essay on blockchain technology

Essay on Blockchain

The advent of the internet is a blessing to mankind. It has now become an integral part of our lives. Internet is required in everything that we do either it is education, traveling, shopping, health, etc. There are several applications of the internet and they are used in different sectors. The use of these applications and technologies reduces the workload and makes the work easier. Blockchain technology has also emerged because of the advent of computers and the internet. This technology came into the limelight after the discovery of cryptocurrency named Bitcoin.

Short and Long Essay on Blockchain in English

This topic is a very interesting topic for students of higher classes and college students. A long elaborated essay on this topic has been provided below. I hope that might aid the students in getting an idea to write an essay on this topic. Moreover, I think that it might be good for all the readers to know about this emerging technology.

10 Lines Essay on Blockchain (100-120 Words)

1) Blockchain is a newer technology that became popular with the emergence of Bitcoin.

2) This technology is used to store data and information.

3) Blockchain is a decentralized system which means no single authority is responsible for managing it.

4) In 2008, Blockchain technology was pushed forward by Satoshi Nakamoto.

5) In this technology, there are different blocks containing information.

6) All the blocks are interconnected and hence it is named Blockchain technology.

7) This technology is highly safe and secured.

8) Any change in the record can be easily identified in this technology.

9) The working and maintenance of Blockchain require huge energy.

10) In Blockchain, if the private key is lost then it is impossible to gain access again.

2000 Words Long Essay- Blockchain : The Distributed Ledger System

Introduction

Blockchain technology is the most discussed topic at present on different forums in the world. Many of us might be familiar with this topic and its details, but there are many among us who would have heard the name of this topic for the first time. It is an interesting topic and we will be discussing Blockchain, its working, origin, types, pros and cons and future scope in the essay provided below.

What is meant by Blockchain?      

Blockchain in simple terms is regarded as the record-keeping technology and has been popular after the advent of Bitcoin. This technology is also linked with banking and investment firms. The information regarding different transactions and details of credit and debit are noted down by us and are termed as records. This is the procedure of maintaining the records manually and the manual records are stated as the ledger. The process of maintaining the record of information and data in form of databases that are stored electronically on the computer system is called Blockchain. It can also be regarded as a digital ledger.

Blockchain is the system of recording and storing information in such a way that it cannot be edited or hacked. Every computer connected to this system has access to the data and information recorded in the Blockchain. It is not managed and controlled by any single person or authority but is decentralized. Thus, the technology is also stated as the distributed ledger system.

Origin of Blockchain Technology

The idea of the protocol of Blockchain at first was suggested by Cryptographer David Chaum in the year 1982. He proposed this idea in his dissertation work on “Computer Systems Established, Maintained, and Trusted by Mutually Suspicious Groups”. Stuart Haber and W. Scott Stornetta were first to start working on the concept of blockchain in the year 1991.  Later there were many attempts made to carry forward this concept.

The concept of Blockchain came into reality in the year 2008 and the credit for inventing this technology goes to Satoshi Nakamoto. He named this technology Block and Chain i.e. it was of two words in his original paper but later the technology was named Blockchain a single word in the year 2016. This technology came into existence after the advent of cryptocurrency called Bitcoin. Nakamoto wanted to create a Bitcoin ledger as a decentralized system that can easily be assessed by the people connected to the system.

How Blockchain Works?

• The information is stored in different blocks that are linked in a sequence and thus this technology is termed Blockchain. Every block in the Blockchain has a limited storage capacity for storing data and information. The blocks, after becoming full with the information, are linked with the other blocks and the information starts being stored in the new blocks.
• The Blockchain is made up of different blocks containing information. Every block in the Blockchain has its own data, cryptographic hash that is unique to every block and the hash of the previous block.
• The hash of the previous block present in every block helps in linking the blocks together to form a Blockchain. The only block that does not have any hash of the previous block is the genesis block. It is formed initially and thus does not have any hash of previous blocks.
• Any attempt to edit data and information stored in blocks results in changing the hash of the block. Thus, change in the hash of one block lead to changes in other linked blocks too. In this way, the change can be easily detected. This causes disruption of data of all blocks in a Blockchain.
• The Blockchain can be assessed by different people linked to this system. The people connected to this system through their computers are termed nodes. Miners among them are the people who are connected to this system and verify the information that is newly added to the blocks. Thereafter, the data is noted and stored in the blocks.
• The information stored in the Blockchain can easily be assessed by the computers linked in the network but the privacy of the data will be maintained throughout this process.
• The information in Blockchain is updated after every ten minutes interval.

Attributes of Blockchain

There are certain features that are specific to the Blockchain technology and are enlisted below:

• A Decentralized Technology- The records of the several transactions and information can be made in excel sheets on computers but there is a difference in the collection of information in Blockchain. The information stored in different blocks in a Blockchain is not only managed by a single person or authority. Every user in the network has a copy of the information on their computers and thus no modification can be made by anyone.
• No Need for Third-Party- There is no any need for a third party to be involved in any kind of interaction between two parties. The interaction and transactions can easily be done by using Blockchain technology.
• Change of Data in the Blocks is Impossible- Any kind of change in the data stored in the blocks is impossible. It is because the change in data of one block results in changing the hash of all subsequent blocks. Therefore, the change in the data stored in the blocks is nearly impossible.
• Change Can Be Detected Easily- The attempt to change information in the blocks can easily be detected by the other users in the network.

Classification of Blockchain Technology

The Blockchain technology network can be broadly be classified into four types of networks and that are stated below:

• Public Blockchain- The public Blockchain is a chain of information that has no restrictions for its access. Any user in the network needs no permission to access the history of Blockchain or carry out any kind of transaction. The information can easily be transferred and accessed by people all around the world on this type of network of Blockchain without any prior permission. Bitcoin Blockchain is an example of a public blockchain. 
• Private Blockchain- This type of Blockchain network needs permission for accessing the information. This type of Blockchain network cannot be joined by anyone without the permission of the owner. The digital ledger in this type of Blockchain is shared among only the trusted members. This type of network is usually managed by different organizations and enterprises.
• Hybrid Blockchain- This type of Blockchain network refers to the mixture of the attributes of both centralized and decentralized blockchains. The working of the hybrid blockchain depends upon the percentage of centralization and decentralization.
• Sidechains- This is the network of blockchain that executes parallel to the primary blockchain. The side chains work independently from the primary blockchain.

Need of Blockchain

The advent of the internet and different technologies has resulted in several digital technologies in the world. Blockchain is a new and emerging concept in society but is becoming popular at a very fast pace. Earlier when there was no such technology the records and information were noted and maintained in the written format by the people. There was a maximum chance of errors when the data was noted manually. Moreover, the data and information could easily be edited easily that later gave rise to corruption.

There is a dire need for a technology like a blockchain that will ensure the security of the recorded data with full transparency. This will also help in gaining the trust of people and they can access the information in the blocks without any kind of fear of cheating.  The copy of the transaction is available on all the computers linked with the blockchain network and this validates the security of the transactions. This technology is preferred by the banks for the process of money transfers, storing records, and different technical works.

Benefits of Blockchain

• The blockchain enables us in getting accurate data on which people can easily rely upon. The private records in blockchains will only be shared with the members of the network who have been granted access by us.
• The transactions that are recorded in the blocks cannot be altered by anybody and any change can easily be detected by the users in the network. This states that this technology is very secure.
• The use of blockchain technology helps in the removal of third-party involvement in transaction and record-keeping processes. There will be no extra charge incurred for the transactions by blockchain technology.
• The data and information can be saved without wasting unwanted time and effort thus blockchain is an efficient technology.

Limitations of Blockchain Technology

• The verification of transactions in blockchain requires huge power or electricity.
• The private key in the blockchain secures Bitcoins and thus it must be kept secret. The knowledge of the private key to the third party means revealing about the Bitcoins to them. Thus, it is necessary to protect these keys from becoming exposed to third parties. These keys if once lost cannot be backed up and money secured in them also gets lost.
• The records and transactions in the blockchains are distributed ledger i.e. it is present on every computer of every user in the network. Any transaction without verification of all the members cannot be entered into the blocks. The verification of the transaction from a large number of users requires time and thus it is a time taking process. This results in a lowering of the transaction speed.

How is Blockchain Essential for Operating Bitcoin?

Bitcoin is a digital currency and it is managed by the Blockchain. There is no authority that is meant for operating the crypto currencies. The transaction of every Bitcoin is stored in the blockchains. Further, the options of the digital currency are distributed on the computers in the network. This facilitates the operating of Bitcoins without the involvement of any kind of central authority. The data of the transactions of Bitcoins are stored in the blocks of the blockchain. This is a risk-free and secure option for operating Bitcoin.

Blockchain Wallet- This is a digital or E-wallet service that is provided by the blockchain company. It enables the users of the blockchain network to store and manage, transfer, and trade cryptocurrencies. The wallet s well provided with the security features that help in reducing the chances of online fraud and thefts.

Applications of Blockchain Technology

• Development of Smart Contacts- Different parties signs contract or agreement for the exchange of services and products in businesses. This happens mainly on paper that is mainly prone to different types of errors and frauds. The development of new technology called smart contacts in blockchains ease this work and help it in making it more secure. This technology performs everything exactly like that takes place on paper. The difference is only that it is digital and can be executed by the user. Moreover, there is no risk of editing data in the blockchain. Thus smart contact can be used for carrying out different financial agreements, storing property documents, crowdfunding, healthcare transactions, etc. Every detail from manufacturing to delivery in the process of exchange of products is maintained by the smart contract.
• Voting and Elections- The process of elections in the nation are carried out manually and thus there are maximum chances of occurrence of errors. The news of some frauds in the elections is very common during the elections in the nation. The introduction of smart contact if introduced in the system of voting and election might reduce the chances of the occurrence of such errors and frauds. This will also help in conducting free and fair elections in the nation.
• Reduce the Chance of Cyber Crimes- The chances of cybercrime are very common nowadays with the fast pace of digitalization. Many people every now and ten are becoming the victim of cyber frauds because while doing online transactions the details are stolen by the hackers. Blockchain technology helps in digitizing the documents that can facilitate the users in doing online transactions and interactions.
• Prevent Copying of Original Contents- The information and articles on different topics are available easily on the websites. This information is many times copied and used by people without the permission of the author of the article. Blockchain technology facilitates the authors to prevent the copyright of their written articles by registering their work online in smart contracts with full privacy. There will be no chances of editing or copying the work of the authors and the authority of the content will be totally restricted in the hands of the owner.

Blockchain is an emerging technology and its use at present is limited only to the crypto currency. This technology is also said to be useful in different sectors in the coming future. It is being tested for the same in different sectors in several countries of the world. It is brought into use in the banking and commerce sectors in different countries. This technology is becoming popular at a very fast pace and there are many fields where it can bring revolutionary changes. The advent of such technology is dire of need in coming future. I have tried to explain the blockchain in a very simple way in form of a long essay. I hope that you will find it interesting and love reading about this new technology.

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FAQs: Frequently Asked Questions on Blockchain

Ans. Blockchain is a system of recording and storing the data with no chance of editing or hacking the information.

Ans. The banking sector is using blockchain technology in India.

Ans. The United States of America USA is the leading country in the world in blockchain technology.

Ans. Japan was the first country in the world to embrace blockchain technology.

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What is blockchain?

Blockchain is one of the major tech stories of the past decade. Everyone seems to be talking about it—but beneath the surface chatter there’s not always a clear understanding of what blockchain is or how it works. Despite its reputation for impenetrability, the basic idea behind blockchain is pretty simple. And it has major potential to change industries from the bottom up .

Blockchain is a technology that enables the secure sharing of information. Data, obviously, is stored in a database. Transactions are recorded in an account book called a ledger. A blockchain is a type of distributed database or ledger—one of today’s top tech trends —which means the power to update a blockchain is distributed between the nodes, or participants, of a public or private computer network. This is known as distributed ledger technology, or DLT. Nodes are incentivized with digital tokens or currency to make updates to blockchains.

Get to know and directly engage with senior McKinsey experts on blockchain

Michael Chui  is a partner at the McKinsey Global Institute and is based in McKinsey’s Bay Area office, where Marie-Claude Nadeau is a senior partner.

Blockchain allows for the permanent, immutable, and transparent recording of data and transactions. This, in turn, makes it possible to exchange anything that has value, whether that is a physical item or something less tangible.

A blockchain has three central attributes . First, a blockchain database must be cryptographically secure. That means in order to access or add data on the database, you need two cryptographic keys: a public key, which is basically the address in the database, and the private key, which is a personal key that must be authenticated by the network.

Next, a blockchain is a digital log or database of transactions, meaning it happens fully online.

And finally, a blockchain is a database that is shared across a public or private network. One of the most well-known public blockchain networks is the Bitcoin blockchain . Anyone can open a Bitcoin wallet or become a node on the network. Other blockchains may be private networks. These are more applicable to banking and fintech , where people need to know exactly who is participating, who has access to data, and who has a private key to the database. Other types of blockchains include consortium blockchains and hybrid blockchains, both of which combine different aspects of public and private blockchains.

Research from the McKinsey Technology Council suggests that by 2027, up to 10 percent of global GDP could be associated with blockchain-enabled transactions. But in the world of blockchain, what is real and what is just hype? And how can companies use blockchain to increase efficiency and create value? Read on to find out.

Learn more about McKinsey’s Financial Services Practice .

How does blockchain work?

A deeper dive may help in understanding how blockchain and other DLTs work .

When data on a blockchain is accessed or altered, the record is stored in a “block” alongside the records of other transactions. Stored transactions are encrypted via unique, unchangeable hashes, such as those created with the SHA-256 algorithm. New data blocks don’t overwrite old ones; they are appended together so that any changes can be monitored. And since all transactions are encrypted, records are immutable—so any changes to the ledger can be recognized by the network and rejected.

These blocks of encrypted data are permanently “chained” to one another, and transactions are recorded sequentially and indefinitely, creating a perfect audit history that allows visibility into past versions of the blockchain.

When new data is added to the network, the majority of nodes must verify and confirm the legitimacy of the new data based on permissions or economic incentives, also known as consensus mechanisms . When a consensus is reached, a new block is created and attached to the chain. All nodes are then updated to reflect the blockchain ledger.

In a public blockchain network , the first node to credibly prove the legitimacy of a transaction receives an economic incentive. This process is called “mining.”

Here’s a theoretical example to help illustrate how blockchain works. Imagine that someone is looking to buy a concert ticket on the resale market. This person has been scammed before by someone selling a fake ticket, so she decides to try one of the blockchain-enabled decentralized ticket exchange websites that have been created in the past few years. On these sites, every ticket is assigned a unique, immutable, and verifiable identity that is tied to a real person. Before the concertgoer purchases her ticket, the majority of the nodes on the network validate the seller’s credentials, ensuring that the ticket is in fact real. She buys her ticket and enjoys the concert.

What is proof of work and how is it different from proof of stake?

Remember the idea of consensus mechanisms mentioned earlier? There are two ways blockchain nodes arrive at a consensus: through private blockchains, where trusted corporations are the gatekeepers of changes or additions to the blockchain, or through public, mass-market blockchains.

Most public blockchains arrive at consensus by either a proof-of-work or proof-of-stake system . In a proof-of-work system, the first node, or participant, to verify a new data addition or transaction on the digital ledger receives a certain number of tokens as a reward. To complete the verification process, the participant, or “miner,” must solve a cryptographic question. The first miner who solves the puzzle is awarded the tokens.

Originally, people on various blockchains mined as a hobby. But because this process is potentially lucrative , blockchain mining has been industrialized. These proof-of-work blockchain-mining pools have attracted attention for the amount of energy they consume.

In September 2022, Ethereum, an open-source cryptocurrency network, addressed concerns around energy usage by upgrading its software architecture to a proof-of-stake blockchain. Known simply as “the Merge,” this event is seen by cryptophiles as a banner moment in the history of blockchain. With proof-of-stake, investors deposit their crypto coins in a shared pool in exchange for the chance to earn tokens as a reward. In proof-of-stake systems, miners are scored based on the number of native protocol coins they have in their digital wallets and the length of time they have had them. The miner with the most coins at stake has a greater chance to be chosen to validate a transaction and receive a reward.

Introducing McKinsey Explainers : Direct answers to complex questions

How can businesses benefit from blockchain.

Research suggests that blockchain and DLTs could create new opportunities for businesses by decreasing risk and reducing compliance costs, creating more cost-efficient transactions, driving automated and secure contract fulfillment, and increasing network transparency. Let’s break it down further:

• Reduced risk and lower compliance costs . Banks rely on “know your customer” (KYC) processes to bring customers on board and retain them. But many existing KYC processes are outdated and drive costs of as much as $500 million per year, per bank. A new DLT system might require once-per-customer KYC verification, driving efficiency gains, cost reduction, and improved transparency and customer experience.
• Cost-efficient transactions. Digitizing records and issuing them on a universal ledger can help save significant time and costs. In a letter-of-credit deal, for example, two companies opted for a paperless solution and used blockchain to trade nearly $100,000 worth of butter and cheese. By doing so, a process that previously took up to ten days was reduced to less than four hours—from issuing to approving the letter of credit.
• Automated and secure contract fulfillment. Smart contracts are sets of instructions coded into tokens issued on a blockchain that can self-execute under specific conditions. These can enable automated fulfillment of contracts. For example, one retailer wanted to streamline its supply-chain-management efforts, so it began recording all processes and actions, from vendor to customer, and coding them into smart contracts on a blockchain. This effort not only made it easier to trace the provenance of food for safer consumption but also required less human effort and improved the ability to track lost products.

Learn more about McKinsey’s  Financial Services Practice .

How are blockchain, cryptocurrency, and decentralized finance connected?

Blockchain enables buyers and sellers to trade cryptocurrencies online  without the need for banks or other intermediaries.

All digital assets, including cryptocurrencies, are based on blockchain technology. Decentralized finance (DeFi)  is a group of applications in cryptocurrency or blockchain designed to replace current financial intermediaries with smart contract-based services. Like blockchain, DeFi applications are decentralized, meaning that anyone who has access to an application has control over any changes or additions made to it. This means that users potentially have more direct control over their money.

What else can blockchain be used for?

Cryptocurrency is only the tip of the iceberg. Use cases for blockchain are expanding rapidly beyond person-to-person exchanges, especially as blockchain is paired with other emerging technology.

Examples of other blockchain use cases include the following:

• With blockchain, companies can create an indelible audit trail through a sequential and indefinite recording of transactions. This allows for systems that keep static records (of land titles, for example) or dynamic records (such as the exchange of assets).
• Blockchain allows companies to track a transaction down to its current status. This enables companies to determine exactly where the data originated and where it was delivered, which helps to prevent data breaches.
• Blockchain supports smart contracts, which are programs that trigger transactions automatically upon fulfillment of contract criteria.

What are some concerns around the future of blockchain?

While blockchain may be a potential game changer , there are doubts emerging about its true business value . One major concern is that for all the idea-stage use cases, hyperbolic headlines, and billions of dollars of investment, there remain very few practical, scalable use cases  of blockchain.

One reason for this is the emergence of competing technologies. In the payments space, for example, blockchain isn’t the only fintech disrupting the value chain—60 percent of the nearly $12 billion invested in US fintechs in 2021 was focused on payments and lending. Given how complicated blockchain solutions can be—and the fact that simple solutions are frequently the best —blockchain may not always be the answer to payment challenges.

Looking ahead, some believe the value of blockchain lies in applications that democratize data, enable collaboration, and solve specific pain points. McKinsey research shows that these specific use cases are where blockchain holds the most potential, rather than those in financial services.

How might blockchain evolve over time?

In the next five years, McKinsey estimates that there will be two primary development horizons for blockchain:

• Growth of blockchain as a service (BaaS). BaaS is a cloud-based service that builds digital products for DLT and blockchain environments without any setup requirements for infrastructure. This is currently being led by Big Tech companies.
• Interoperability across blockchain networks and outside systems. Increased interoperability will mean that disparate blockchain networks and external systems will be able to view, access, and share one another’s data while maintaining integrity. Hardware standardization and scalable consensus algorithms will enable cross-network use cases—such as the Internet of Things  on blockchain infrastructure.

These trends will be enabled partly because of increased pressure from regulators and consumers demanding greater supply chain transparency, and partly because of economic uncertainty, as consumers seek out independent, centrally regulated systems. And large corporations launching successful pilots will build confidence for consumers and other organizations.

Potential growth could be inhibited by a few factors: for one, several well-known applications have inherently limited scalability, including energy or infrastructure requirements. Further, uncertainty about regulatory or governance developments could keep consumers shy—for instance, if there is a lack of clarity on who will enforce smart contracts. And, finally, the unresolved threat of cyberattacks remains a fear for potential blockchain users.

What do NFTs have to do with blockchain?

Nonfungible tokens (NFTs) are minted on smart-contract blockchains such as Ethereum or Solana. NFTs represent unique assets that can’t be replicated—that’s the nonfungible part—and can’t be exchanged on a one-to-one basis. These assets include anything from a Picasso painting to a digital lolcat meme. Because NFTs are built on top of blockchains, their unique identities and ownership can be verified through the ledger. With some NFTs, the owner receives a royalty every time the NFT is traded.

The NFT market is extremely volatile : in 2021, one NFT created by the digital artist Mike Winkelmann, also known as Beeple, was sold  at Christie’s for $69.3 million. But NFT sales have shrunk dramatically since summer 2022.

How secure is blockchain?

Blockchain has been called a “ truth machine .” While it does eliminate many of the issues that arose in Web 2.0, such as piracy and scamming, it’s not the be-all and end-all for digital security. The technology itself is essentially foolproof, but, ultimately, it is only as noble as the people using it and as good as the data they are adding to it.

A motivated group of hackers could leverage blockchain’s algorithm to their advantage by taking control of more than half of the nodes on the network. With this simple majority, the hackers have consensus and thus the power to verify fraudulent transactions.

In 2022, hackers did exactly that, stealing more than $600 million from the gaming-centered blockchain platform Ronin Network. This challenge, in addition to the obstacles regarding scalability and standardization, will need be addressed. But there is still significant potential for blockchain, both for business and society.

For a more in-depth exploration of these topics, see McKinsey’s “ Blockchain and Digital Assets ” collection. Learn more about McKinsey’s Financial Services Practice —and check out blockchain-related job opportunities if you’re interested in working at McKinsey.

Articles referenced include:

• “ McKinsey Technology Trends Outlook 2022 ,” August 24, 2022
• “ Forward Thinking on tech and the unpredictability of prediction with Benedict Evans ,” April 6, 2022, Janet Bush and Michael Chui
• “ Seven technologies shaping the future of fintech ,” November 9, 2021, Dick Fong, Feng Han, Louis Liu, John Qu, and Arthur Shek
• “ CBDC and stablecoins: Early coexistence on an uncertain road ,” October 11, 2021, Ian De Bode, Matt Higginson , and Marc Niederkorn
• “ Blockchain and retail banking: Making the connection ,” June 7, 2019, Matt Higginson , Atakan Hilal, and Erman Yugac
• “ Blockchain 2.0: What’s in store for the two ends—semiconductors (suppliers) and industrials (consumers)? ,” January 18, 2019, Gaurav Batra, Rémy Olson, Shilpi Pathak, Nick Santhanam, and Harish Soundararajan
• “ Blockchain’s Occam problem ,” January 4, 2019, Matt Higginson , Marie-Claude Nadeau , and Kausik Rajgopal
• “ Blockchain explained: What it is and isn’t, and why it matters ,” September 28, 2018

Want to know more about blockchain?

Related articles.

Blockchain’s Occam problem

Blockchain beyond the hype: What is the strategic business value?

Blockchain explained: What it is and isn’t, and why it matters

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Annual Report 2021

Federal Reserve Bank of St. Louis

The Blockchain Revolution: Decoding Digital Currencies

By David Andolfatto and Fernando M. Martin

• Introduction

Few people took notice of an obscure white paper published in 2009 titled “Bitcoin: A Peer-to-Peer Electronic Cash System,” authored by a pseudonymous Satoshi Nakamoto. The lack of fanfare at the time is hardly surprising given that innovations in the way we make payments are not known to generate tremendous amounts of excitement, let alone inspire visions of a revolution in finance and corporate governance. But just over a decade later, the enthusiasm for cryptocurrencies and decentralized finance spawned by Bitcoin and blockchain technology has grown immensely and shows no signs of abating.

Because cryptocurrencies are money and payments systems, they have naturally drawn the interest of central banks and regulators. The Federal Reserve Bank of St. Louis was the first central banking organization to sponsor a public lecture on the topic: In March 2014, presenters outlined the big picture of cryptocurrencies and the blockchain by discussing its possibilities and pitfalls. Since that time, the Bank’s economists and research associates have published numerous articles and explainers on these topics, all of which are freely available to the general public. This essay represents a continuation of our effort to help educate the public and offer our perspective of the phenomenon as central bankers and economists.

Understanding how cryptocurrencies work “under the hood” is a challenge for most people because the protocols are written in computer code and the data are managed in an esoteric mathematical structure. To be fair, it’s difficult to understand any technical language (e.g., legalese, legislation and regulation). Because we are not technical experts in this space, we spend virtually no time discussing the technology in detail. For an accessible introduction to the technology, see Fabian Schär and Aleksander Berentsen’s “ Bitcoin, Blockchain, and Cryptoassets: A Comprehensive Introduction ,” MIT Press, 2020. What we offer instead is an overview of cryptocurrencies and blockchain technologies, explaining the spirit of the endeavor and how it compares with traditional operations.

In this essay, we explore four key areas:

• Money, digital money and payments
• Cryptocurrencies, blockchain and the double-spend problem of digital money
• Understanding decentralized finance
• The makeup of a central bank digital currency
• Money, Digital Money and Payments

It is sometimes said that money is a form of social credit. One can think of this idea in the following way: When people go to work, they are in effect providing services to the community. They are helping to make others’ lives better in some way and, by engaging in this collective effort, make their own lives better as well.

In small communities, individual consumption and production decisions can be debited and credited, respectively, in a sort of communal ledger of action histories. This is because it is relatively easy for everyone to monitor and record individual actions. A person who has produced mightily for the group builds social credit. Large social credit balances can be “spent” later as consumption (favors drawn from other members of the community).

In large communities, individual consumption and production decisions are difficult to monitor. In communities the size of cities, for example, most people are strangers. Social credit based on a communal record-keeping system does not work when people are anonymous. See Narayana Kocherlakota’s “ The Technological Role of Fiat Money ,” Federal Reserve Bank of Minneapolis, Quarterly Review , 1998. Producers are rewarded for their efforts by accumulating money balances in wallets or bank accounts. Accumulated money balances can then be spent to acquire goods and services (or assets) from other members of the community, whose wallets and bank accounts are duly credited in recognition of their contributions. In this manner, money—like social credit—serves to facilitate the exchange of goods and services.

The monetary object representing this social credit may exist in physical or nonphysical form. In the United States, physical cash takes the form of small-denomination Federal Reserve bills and U.S. Treasury coins. Cash payments are made on a peer-to-peer (P2P) basis, for example, between customer and merchant. No intermediary is required for clearing and settling cash payments. As the customer debits his or her wallet, cash is credited to the merchant’s cash register, and the exchange is settled. Hardly any time is spent inspecting goods and money in small-value transactions. Some trust is required, of course, in the authority issuing the cash used in transactions. While that authority is typically the U.S. government, there is no law preventing households and businesses from accepting, say, foreign currency, gold or any other object as payment.

When people hear the word “money,” they often think of cash. But, in fact, most of the U.S. money supply consists of digital dollars held in bank accounts. The digital money supply is created as a byproduct of commercial bank lending operations and central bank open market operations. Digital money is converted into physical form when depositors choose to withdraw cash from their bank accounts. Most people hold both forms of money. The reasons for preferring one medium of exchange over the other are varied and familiar.

Digital dollar deposits in the banking system are widely accessible by households and businesses. This digital money flows in and out of bank accounts in the form of credits and debits whenever a party initiates a purchase. Unlike with cash, making payments with digital money has traditionally required the services of a trusted intermediary. A digital money payment is initiated when a customer sends an encrypted message instructing his or her bank to debit the customer’s account and credit the merchant’s account with an agreed-upon sum. This debit-credit operation is straightforward to execute when both customer and merchant share the same bank. The operation is a little more complicated when the customer and merchant do not share the same bank. In either case, clearing and settling payments boils down to an exercise in secure messaging and honest bookkeeping.

• Cryptocurrencies, Blockchain and the Double-Spend Problem of Digital Money

One can think of cryptocurrencies as digital information transfer mechanisms. If the information being transferred is used as an everyday payment instrument, it fulfills the role of money. In this case, a cryptocurrency can be thought of as a money and payments system.

Every money and payments system relies on trust. The difference between cryptocurrencies and conventional money and payments systems lies in where this trust is located. In contrast to conventional systems, no delegated legal authority is responsible for managing and processing cryptocurrency information. Instead, the task is decentralized and left open to “volunteers” drawn from the community of users, similar in spirit to how the internet-based encyclopedia Wikipedia is managed. These volunteers—called miners—work to update and maintain a digital ledger called the blockchain. The protocols that govern the read-write privileges associated with the blockchain are enshrined in computer code. Users trust that these rules are not subject to arbitrary changes and that rule changes (if any) will not benefit some individuals at the expense of the broader community. Overall, users must trust the mathematical structure embedded in the database and the computer code that governs its maintenance.

Managing a digital ledger without a delegated accounts manager is not a trivial problem to solve. If just anyone could add entries to a public ledger, the result likely would be chaos. Malevolent actors would be able to debit an account and credit their own at will. Or they could create social credit out of thin air, without having earned it. In the context of money and payments systems, these issues are related to the so-called double-spend problem.

To illustrate the double-spend problem, consider the example of a dollar stored in a personal computer as a digital file. It is easy for a customer to transfer this digital file to a merchant on a P2P basis, say, by email. The merchant is now in possession of a digital dollar. But how can we be sure that the customer did not make a copy of the digital file before spending it? It is, in fact, a simple matter to make multiple copies of a digital file. The same digital file can then be spent twice (hence, a double-spend). The ability to make personal copies of digital money files would effectively grant each person in society his or her own money printing press. A monetary system with this property is not likely to function well.

Physical currency is not immune from the double-spend problem, but paper bills and coins can be designed in a manner to make counterfeiting sufficiently expensive. Because cash is difficult to counterfeit, it can be used more or less worry-free to facilitate P2P payments. The same is not true of digital currency, however. The conventional solution to the double-spend problem for digital money is to delegate a trusted third party (e.g., a bank) to help intermediate the transfer of value across accounts in a ledger. Bitcoin was the first money and payments system to solve the double-spend problem for digital money without the aid of a trusted intermediary. How?

The Digital Village: Communal Record-Keeping

The cryptocurrency model of communal record-keeping resembles the manner in which history has been recorded in small communities, including in networks of family and friends. It is said that there are no secrets in a small village. Each member of the community has a history of behavior, and this history is more or less known by all members of the community—either by direct observation or through communications. The history of a small community can be thought of as a virtual database living in a shared (or distributed) ledger of interconnected brains. No one person is delegated the responsibility of maintaining this database—it is a shared responsibility.

Among other things, such a database contains the contributions that individuals have made to the community. As we described above, the record of these contributions serves as a reputational history on which individuals can draw; the credit they receive from the community can be considered a form of money. There is a clear incentive to fabricate individual histories for personal gain—the ability to do so would come at the expense of the broader community in the same way counterfeiting money would. But open, shared ledgers are very difficult to alter without communal consensus. This is the basic idea behind decentralized finance, or DeFi.

Governance via Computer Code

All social interaction is subject to rules that govern behavior. Behavior in small communities is governed largely by unwritten rules or social norms. In larger communities, rules often take the form of explicit laws and regulations. At the center of the U.S. money and payments system is the Federal Reserve, which was created in 1913 through an act of Congress. The Federal Reserve Act of 1913 specifies the central bank’s mandates and policy tools. There is also a large body of legislation that governs the behavior of U.S. depository institutions. While these laws and regulations create considerable institutional inertia in money and payments, the system is not impervious to change. When there is sufficient political support—feedback from the American people—changes to the Federal Reserve Act can be made. The Humphrey-Hawkins Act of 1978 , for example, provided the Fed with three mandates: stable prices, maximum employment and moderate long-term interest rates. And the Dodd-Frank Act of 2010 imposed stricter regulations on financial firms following the financial crisis in 2007-09.

Because cryptocurrencies are money and payments systems, they too must be subject to a set of rules. In 2009, Satoshi Nakamoto brought forth his aforementioned white paper, which laid out the blueprint for Bitcoin. This blueprint was then operationalized by a set of core developers in the form of an open-source computer program governing monetary policy and payment processing protocols. Adding, removing or modifying these “laws” governing the Bitcoin money and payments system is virtually impossible. Relatively minor patches to the code to fix bugs or otherwise improve performance have been implemented. But certain key parameters, like the one that governs the cap on the supply of bitcoin, are likely impervious to change.

Concerted attempts to change the protocol either fail or result in breakaway communities called “forks” that share a common history with Bitcoin but otherwise go their separate ways. Proponents of Bitcoin laud its regulatory system for its clarity and imperviousness, especially relative to conventional governance systems in which rules are sometimes vague and subject to manipulation.

Bitcoin: Beyond the Basics

Learn about the structure and fundamentals of Bitcoin in this Timely Topics podcast with St. Louis Fed economist David Andolfatto. During the 16-minute episode , Andolfatto examines how distributed ledgers work and explains the mining process. This podcast was released Aug. 27, 2018.

How Blockchain Technology Works

As with any database management system, the centerpiece of operations is the data itself. For cryptocurrencies, this database is called the blockchain. One can loosely think of the blockchain as a ledger of money accounts, in which each account is associated with a unique address. These money accounts are like post office boxes with windows that permit anyone visiting the post office to view the money balances contained in every account. Beyond viewing the balances, one can also view the transaction histories of every monetary unit in the account (i.e., its movement from account to account over time since it was created). These windows are perfectly secured. It is important to note that many cryptocurrency users hold their funds via third parties to whom they relinquish control of their private keys. If an intermediary is hacked and burgled, one’s cryptocurrency holdings may be stolen. This has nothing to do with security flaws in the cryptocurrency itself—but with the security flaws of the intermediary. While anyone can look in, no one can access the money without the correct password. This password is created automatically when the account is opened and known only by the person who created the account (unless it is voluntarily or accidentally disclosed to others). The person’s account name is pseudonymous (unless voluntarily disclosed). These latter two properties imply that cryptocurrencies (and cryptoassets more generally) are digital bearer instruments. That is, ownership control is defined by possession (in this case, of the private password). It is worth noting that large-denomination bearer instruments are now virtually extinct. Today, bearer instruments exist primarily in the form of small-denomination bills and metal coins issued by governments. For this reason, cryptocurrencies are sometimes referred to as “digital cash.”

As with physical cash, no permission is needed to acquire and spend cryptoassets. Nor is it required to disclose any personal information when opening an account. Anyone with access to the internet can download a cryptocurrency wallet—software that is used to communicate with the system’s miners (the aforementioned volunteer accountants). The wallet software simultaneously generates a public address (the “location” of an account) and a private key (password). Once this is done, the front-end experience for consumers to initiate payment requests and manage money balances is very similar to online banking as it exists today. Of course, if a private key is lost or stolen, there is no customer service department to call and no way to recover one’s money.

Cryptocurrencies have become provocative and somewhat glamorous, but their unique and key innovation is how the database works. The management of money accounts is determined by a set of regulations (computer code) that determines who is permitted to write to the database. The protocols also specify how those who expend effort to write to the database—essentially, account managers—are to be rewarded for their efforts. Two of the most common protocols associated with this process are called proof-of-work (PoW) and proof-of-state (PoS). The technical explanation is beyond the scope of this essay. Suffice it to say that some form of gatekeeping is necessary—even if the effort is communal—to prevent garbage from being written to the database. The relevant economic question is whether these protocols, whatever they are, can process payments and manage money accounts more securely, efficiently and cheaply than conventional centralized finance systems.

Native Token

Recording money balances requires a monetary unit. This unit is sometimes referred to as the native token. From an economic perspective, a cryptocurrency’s native token looks like a foreign currency, albeit one whose monetary policy is governed by a computer algorithm rather than the policymakers of that country. Much of the excitement associated with cryptocurrencies seems to stem from the prospect of making money through capital gains via currency appreciation relative to the U.S. dollar (USD). (To see how the prices of bitcoin and ethereum, another cryptocurrency, have changed over the past decade, see the FRED charts below.) It seems to have less to do with the promise of the underlying record-keeping technology stressed by Nakamoto’s white paper. To be sure, the price of a financial security can be related to its underlying fundamentals. It is not, however, entirely clear what these fundamentals are for cryptocurrency or how they might generate continued capital gains for investors beyond the initial rapid adoption phase. Moreover, while the supply of a given cryptocurrency such as Bitcoin may be capped, the supply of close substitutes (from the perspective of investors, not users) is potentially infinite. Thus, while the total market capitalization of cryptocurrencies may continue to grow, this growth may come more from newly created cryptocurrencies and not from growth in the per-unit price of any given cryptocurrency, such as Bitcoin. See David Andolfatto and Andrew Spewak’s “ Whither the Price of Bitcoin? ” Federal Reserve Bank of St. Louis, Economic Synopses , 2019.

SOURCE: Coinbase, retrieved from FRED (Federal Reserve Economic Data).

NOTE: Gray shaded areas indicate U.S. recessions. For more data from Coinbase, see these series .

In any case, conceptually, there is a distinction to be made between the promise of a cryptocurrency’s underlying technology and the market price of its native token. Bitcoin (BTC) as a payments system could, in principle, function just as well at any given BTC/USD exchange rate.

Cryptocurrency Applications

Cryptocurrencies designed to serve as money and payments systems have continued to struggle in their quest for adoption as an everyday medium of exchange. Their main benefit to this point—at least for early adopters—has been as a long-term store of value. But their exchange rate volatility makes them highly unsuitable as domestic payment instruments, given that prices and debt contracts are denominated in units of domestic currency. While year-over-year returns can be extraordinary, it is not uncommon for a cryptocurrency to lose most of its value over a relatively short period of time. How a cryptocurrency might perform as a domestic payments system when it is also the unit of account remains to be seen. El Salvador recently adopted bitcoin as its legal tender, and people will be watching this experiment closely. Legal tender is an object that creditors cannot legally refuse as payment for debt. While deposits are claims to legal tender (they can be converted into cash on demand), they also constitute claims against all bank assets in the event of bankruptcy.

A use case touted early in Bitcoin history was its potential to serve as a vehicle currency for international remittances. One of the attractive attributes of Bitcoin is that anyone with access to the internet can access the Bitcoin payments system freely and without permission. For example, a Salvadoran working in the United States can convert his or her USD into BTC at an online exchange and send BTC to a relative in El Salvador in minutes for (usually) a relatively low fee, compared with sending money through conventional channels.

As with any tool, bitcoin may be used for good or ill purposes. Because BTC is a permissionless bearer instrument (like physical cash), it may become a popular way to finance illegal activities, terrorist organizations and money laundering operations. Recently, it has been used in ransomware attacks, in which nefarious agents blackmail hapless victims and demand payment in bitcoin, thereby bypassing the banking system.

But possibly the most attractive characteristic of Bitcoin is that it operates independently of any government or concentration of power. Bitcoin is a decentralized autonomous organization (DAO). Its laws and regulations exist as open-source computer code living on potentially millions of computers. The blockchain is beyond the (direct) reach of government interference or regulation. There is no physical location for Bitcoin. It is not a registered business. There is no CEO. Bitcoin has no (conventional) employees. The protocol produces a digital asset, the supply of which is, by design, capped at 21 million BTC. Participation is voluntary and permissionless. Large-value payments can be made across accounts quickly and cheaply. It is not too difficult to imagine how these properties can be attractive to many people.

Policy Considerations of Cryptocurrency

To a central bank, a cryptocurrency looks very much like a foreign currency. From this perspective, there is nothing revolutionary here. Foreign currency is sometimes seen as a threat by governments. This is not the case for the United States, since the U.S. dollar remains the world’s reserve currency, but many other countries often take measures to discourage the domestic use of foreign currency. Citizens may be prohibited, for example, from holding foreign currency or opening accounts in foreign banks. Because cryptocurrencies are freely available and permissionless, it would likely be considerably more difficult to enforce cryptocurrency controls. The cryptocurrency option may also serve to constrain domestic monetary and fiscal policies—in particular, by imposing a more stringent limit on the amount of seigniorage (i.e., the “printing” of more money to finance government spending).

A dominant foreign currency may cause another problem: As it turns out, it is often cheaper to issue debt denominated in a dominant foreign currency. The problem with this activity is that when the domestic currency depreciates, debtors may have trouble repaying, and a financial crisis may ensue. When that dominant foreign currency is the U.S. dollar, the central bank of a foreign country can sometimes find relief by borrowing dollars from the Federal Reserve through a currency-swap line. But if debt instruments are denominated in cryptocurrency, there is no negotiating with the DAO of that cryptocurrency. Because this is the case, domestic regulators might want to regulate the practice of issuing cryptocurrency-denominated debt more stringently, if the practice ever became sufficiently widespread to pose significant systemic risk.

• Understanding Decentralized Finance

Decentralized finance broadly refers to financial activities that are based on a blockchain. Unlike conventional or traditional finance that relies on intermediaries and centralized institutions, DeFi relies on so-called smart contracts. The removal of those intermediaries in transactions between untrusted parties would significantly reduce costs and grant the parties more control over the terms of such agreements. Still, intermediaries oftentimes play meaningful roles beyond verification and enforcement, which means they would not altogether disappear. Here, we examine some of these concepts to explain what DeFi means and implies. For a more extensive review, see Fabian Schär’s “ Decentralized Finance: On Blockchain- and Smart Contract-Based Financial Markets ,” Federal Reserve Bank of St. Louis, Review , 2021; also see an analysis by Sara Feenan et al. in “ Decentralized Financial Market Infrastructures: Evolution from Intermediated Structures to Decentralized Structures for Financial Agreements ,” The Journal of FinTech , 2021.

What Are the Benefits and Challenges of Decentralized Finance?

DeFi allows parties to engage in financial transactions without the need for intermediaries. In this short video, St. Louis Fed economist Fernando Martin looks at how DeFi works with smart contracts and digital tokens.

What Are Smart Contracts?

A smart contract is a computer program designed to execute an agreed-upon set of actions. The concept was first introduced in the mid-1990s by Nick Szabo, who proposed vending machines as a primitive example: A vending machine is a mechanism that dispenses a product in exchange for a listed amount of coins (or bills); anyone with a sufficient amount of money can participate in this exchange. See Nick Szabo’s “ Smart Contracts ” (1994) and “ The Idea of Smart Contracts ” (1997). The key idea is that contractual terms, once agreed upon, are not renegotiable and are therefore automatically executed in the future. In economic theory, so-called Arrow-Debreu securities have the same property. Smart contracts allow interested parties to engage in secure financial transactions without the participation of third parties. As we explain below, their application goes beyond conventional financial transactions.

Ethereum is a blockchain with smart contract capability that was released in 2015. In this case, smart contracts are a type of account, with their own balance and the capability to interact with the network. Rather than being controlled by a user, smart contracts run as programmed, with their code and data residing at a specific address on the Ethereum blockchain. Other platforms may implement smart contracts in different ways. For example, Hyperledger allows for confidential transactions, whereas Ethereum, a public network, does not. Bitcoin is also able to handle a variety of smart contracts.

Like cryptocurrencies, smart contracts overcome security and transparency concerns in transactions between untrusted parties, without the need for a trusted third party. In fact, smart contracts aim to do away with intermediaries such as brokers, custodians and clearinghouses.

Consider a collateralized loan as an example. In traditional finance, a borrower seeks a bank to lend funds or a broker to find potential lenders. The parties then agree on the terms of the loan: interest rate, maturity, type and value of collateral, etc. The borrower’s collateral is placed in escrow. If the borrower fulfills the terms of the contract, the collateral is released and full ownership rights are returned. If the borrower defaults, the collateral is used to fulfill the contract (e.g., repay the remaining principal, interest and penalties). There are many parties involved in this transaction: financial intermediaries, appraisers, loan servicers, asset custodians, and others.

In a smart contract, the entire agreement is specified as part of the computer program and is stored on a blockchain. The program contains the terms of the loan, as well as the specific actions it will take based on compliance (e.g., the transfer of collateral ownership in the event of default). Since the blockchain handles the faithful execution of the contract, there is no need to involve any parties beyond the borrower and lender.

Asset Tokenization

The example above illustrates an important wrinkle: It may not be possible for all the elements and actions of a contract to be handled by the blockchain—particularly when it comes to collateral. If collateral is not available as an asset in the native protocol (i.e., the specific blockchain where the smart contracts exist), then, as in traditional finance, the contract necessitates a third party to provide escrow services. Naturally, this exposes the contract to counterparty risk. One solution to this problem is asset tokenization.

Asset tokenization consists of converting the ownership of an asset into digital tokens, each representing a portion of the property. If the asset exists in physical form (e.g., a house), then tokenization allows the asset to exist in a blockchain and be used for various purposes (e.g., as collateral). An important issue is how to enforce property rights stored in the blockchain for assets that exist in the physical world. This is an ongoing challenge for DeFi and one that may never be fully resolved.

Tokens also have a variety of nonfinancial applications. For example, they may grant owners voting rights to an organization. This allows for the decentralized control of institutions within a blockchain, as we describe below. Another popular application is the creation of nonfungible tokens (NFTs), which provide ownership of a digital image created and “signed” by an artist. Although the image could in principle be replicated countless times, there is only one version that is verifiably authentic. The NFT serves as a certificate of authenticity in the same way that artists’ signatures ensure paintings are originals and not copies. The advantage of an NFT is the security provided by the blockchain—signatures can be forged, whereas the authenticity of the NFT is validated by a decentralized communal consensus algorithm.

Decentralized Autonomous Organization

Smart contracts could transform the way we organize and control institutions. Applications may range from investment funds to corporations and perhaps even the provision of public goods and services.

A decentralized autonomous organization, or DAO, is an organization represented by a computer code, with rules and transactions maintained on a blockchain. Therefore, DAOs are governed by smart contracts. A popular example is MakerDAO, the issuer of the stablecoin Dai, whose stakeholders use tokens to help govern decisions over protocol changes.

The concept of governance refers to the rules that balance the interests of different stakeholders of an institution. For example, a corporation’s stakeholders may include shareholders, managers, creditors, customers, employees, the government and the general public, among others. The board of directors typically plays the critical role in corporate governance. One of the main issues corporate governance is designed to mitigate is agency problems: when managers do not act in the best interest of shareholders. But governance extends beyond regulating internal matters and may, for example, manage the role of a corporation inside a community or relative to the environment.

DAOs may be created for ongoing projects, such as a DeFi entity, or for specific and limited purposes, such as public works. Because they offer an alternative governance model by encoding rules in a smart contract, they replace the traditional top-down structure with a decentralized consensus-based model. Two prominent examples—the decentralized exchange Uniswap and the borrowing and lending platform Aave—started out in the traditional way, by having their respective development teams in charge of day-to-day operations and development decisions. They eventually issued their own tokens, which distributed governance to the wider community. With varying details, holders of governance tokens may submit development proposals and vote on them.

Centralized and Decentralized Exchanges

Currently, the most popular way in which cryptoassets are traded is through a centralized exchange (CEX), which works like a traditional bank or a broker: A client opens an account by providing personal identifiable information and depositing funds. With an account, the client can trade cryptoassets at listed prices in the exchange. The client does not own these assets, however, as the exchange acts as a custodian. Hence, clients’ trades are recorded on the exchange’s database rather than on a blockchain. Binance and Coinbase are CEXs that offer accessibility to users. However, since they stand between users and blockchains, they need to overcome the same trust and security issues as traditional intermediaries.

Decentralized exchanges (DEXs), on the other hand, rely on smart contracts to enable trading among individuals on a P2P basis, without intermediaries. Traders using DEXs keep custody of their funds and interact directly with smart contracts on a blockchain.

One way to implement a DEX is to apply the methods from traditional finance and rely on order books. These order books consist of lists of buy and sell orders for a specific security that display the amounts being offered or bid on at each price point. CEXs also work in this way. The difference with DEXs is that the list and transactions are handled by smart contracts. Order books can be “on-chain” or “off-chain,” depending on whether the entire operation is handled on the blockchain. In the case of off-chain order books, typically only the final transaction is settled on the blockchain.

Order-book DEXs may suffer from slow execution and a lack of liquidity. That is, buyers and sellers may not find adequate counterparties, and individual transactions may affect prices too much. DEX aggregators alleviate this problem by collecting the liquidity of various DEXs, which increases the depth of both sides of the market and minimizes slippage (i.e., the difference between the intended and executed price of an order).

An automated market maker (AMM) is another way to solve the liquidity problem in DEXs. Market makers are also derived from traditional finance, where they play a central role in ensuring adequate liquidity in securities markets. AMMs create liquidity pools by rewarding users who “deposit” assets in the smart contract, which then can be used for trades. When a trader proposes an exchange of two assets, the AMM provides an instant quote based on the relative availability (i.e., liquidity) of each asset. When the liquidity pools are sufficiently large, trades are easy to fulfill and slippage is minimized. Automated market makers are currently the dominant form of DEXs, because they resolve the liquidity problem better than alternative mechanisms and thus provide speedier and cheaper transactions.

What Are Stablecoins?

As we described earlier, cryptocurrencies are subject to extreme exchange rate volatility, which makes them highly unsuitable as payment instruments. A stablecoin is a cryptocurrency that ties its value to an asset outside of its control, such as the U.S. dollar. Some stablecoins stabilize their value by pegging to the U.S. dollar, backed with non-U.S. dollar assets; Dai, for example, pegs its value to a senior tranche of other cryptoassets. See Dankrad Feist’s “ On Supply and Demand for Stablecoins ,” 2021. To accomplish this, the stablecoin must effectively convince its liability holders that its liabilities can be redeemed on demand (or on short notice) for U.S. dollars at par (or at some other fixed exchange rate). The purpose of this structure is to render stablecoin liabilities more attractive as payment instruments. Pegging to the U.S. dollar is attractive to people living in the U.S. because the U.S. dollar is the unit of account. Those outside the U.S. may be attracted to the product because the U.S. dollar is the world’s reserve currency. This structure serves to increase demand for the stablecoin. But why would someone want to make U.S. dollar payments using a stablecoin instead of a regular bank account?

The answer ultimately rests on which product offers its clients the services they desire at a price they find attractive. A stablecoin is likely to be attractive at the wholesale level, where firms would be able to make USD payments at each point in an international supply chain without the need for conventional banking arrangements. Stablecoins market themselves as leveraging blockchain technology to deliver safer and more efficient account management and payment processing services. These efficiency gains can then be passed along to customers in the form of lower fees. A more cynical view ascribes these purported lower costs to regulatory arbitrage (i.e., sidestepping certain costs by relocating the transaction outside of the regulatory environment), rather than technological improvements in database management.

A Primer on Stablecoins

Stablecoins are cryptocurrencies that tie their value to an outside asset. In this short video, St. Louis Fed economist Fernando Martin takes a deep dive into stablecoins and how they have characteristics that are similar to money market mutual funds.

Financial Stability Concerns

U.S. dollar-based stablecoins are similar to money market funds that peg the price of their liabilities to the U.S. dollar. They also look very much like banks without deposit insurance . As the financial crisis of 2007-09 showed, even money market funds are subject to runs when the quality of their assets is questioned. Unless a U.S. dollar-based stablecoin is backed fully by U.S. dollar reserves (it needs an account at the Federal Reserve for this) or by U.S. dollar bills (the maximum denomination is $100, so this seems unlikely), it is potentially prone to a bank run. If a stablecoin cannot dispose of its assets at fair or normal prices, it may fail to raise the U.S. dollars it needs to meet its par redemption promise in the face of a wave of redemptions. In such an event, the stablecoin would turn out to be not so stable.

If the adverse consequences of a stablecoin run were limited to the owners of stablecoins, then standard consumer protection legislation would be sufficient. But regulators also are concerned about the possibility of systemic risk. Consider, for example, the commercial paper market, where firms regularly borrow money on a short-term basis to fund operating expenses. Then consider a stablecoin (or any money market fund) with large holdings of commercial paper. A stablecoin run in this case may compel a fire sale of commercial paper to raise the funds needed to meet the wave of redemptions. This fire sale would likely have adverse economic consequences for firms that make regular use of the commercial paper market: As commercial paper prices decline, the value of commercial paper as collateral falls, and firms may find it more difficult to borrow the funds they normally access with ease. If the fire sale spills over into other securities markets, credit conditions may tighten significantly and lead to the usual woes experienced in an economic recession (missed payments, worker layoffs, etc.). These events are sufficiently difficult for a central bank to handle when the entities involved are domestic money market funds. The problem is compounded if the stablecoin is an unregulated “offshore” DAO. Will offshore stablecoins that are “too big to fail” be able to take advantage of the implicit insurance provided by central bank lender-of-last-resort operations? If so, this would be an example of how the private benefits of DeFi arise from regulatory arbitrage and not from an inherent technological advantage. This possibility presents a significant challenge for national and international regulators.

On the other hand, it may be possible for stablecoins to be rendered “run-proof” by employing smart contracts to design more resilient financial structures. For example, real-time communal monitoring of balance sheet positions is a possibility—a feature that could shine light on what are traditionally opaque financial structures. The opacity of financial structures is not necessary to explain bank runs. For example, the canonical model of bank runs assumes the existence of transparent balance sheets. See Douglas Diamond and Philip Dybvig’s “ Bank Runs, Deposit Insurance, and Liquidity ,” The Journal of Political Economy , 1983. Furthermore, because redemption policies can potentially manifest themselves as computer code, their design can be made more elaborate (state-contingent) and credible (contractual terms that can be credibly executed and not reversed). These features can potentially render stablecoins run-proof in a manner that is not possible with conventional banking arrangements. 

Regulators and Stablecoins

The regulatory concerns with stablecoins are similar to age-old concerns with the banking industry. Banks are in the business of creating money and do so by issuing deposit liabilities that promise a fixed (par) exchange rate against U.S. dollar bills and dollar credits held in Federal Reserve accounts. Lower-yielding liabilities are used to acquire higher-yielding assets. Because commercial banks normally hold only a very small fraction of their assets in the form of reserves, they are called fractional reserve banks. Since the introduction of federal deposit insurance, retail-level bank runs have been practically nonexistent. Banks also have access to the Federal Reserve’s emergency lending facilities. These privileges are matched by a set of regulatory constraints on bank balance sheets (both assets and liabilities) and other business practices.

Some stablecoin issuers would undoubtedly like to base their business models on those of banks or prime institutional money market funds. The motivation is clear: Issuing low-cost liabilities to finance high-yielding assets can be a profitable business. (Until, of course, something goes wrong. Then, regulators and policymakers face blame for permitting such structures to exist in the first place.) This business model naturally involves non-negligible risk and could make for a potentially unstable stablecoin. As stablecoins with these properties interact with off-chain financial activity, they introduce risks that may spill over to other markets and, therefore, prompt some form of regulation.

Other stablecoin issuers are likely to focus on delivering payment services, which can be accomplished by holding only safe assets. These stablecoins would be more akin to government money market funds. Stablecoins that submit to government regulations may be permitted to hold only the safest of securities (e.g., U.S. Treasury securities). If they could, they might even hold only interest-bearing reserves, thereby becoming “narrow banks.” The business model in these cases would be based on generating profits through transaction-processing fees and/or net interest margins enhanced by what stablecoin users would hope to be a wafer-thin capital requirement.

• The Makeup of a Central Bank Digital Currency

The Board of Governors of the Federal Reserve System, in its recent paper “ Money and Payments: The U.S. Dollar in the Age of Digital Transformation ,” defines a central bank digital currency (CBDC) as a “digital liability of the Federal Reserve that is widely available to the general public.” This essentially means allowing the general public to open personal bank accounts at the central bank. How might a CBDC work?

Today, only financial institutions defined as depository institutions by the Federal Reserve Act and a select number of other agencies (including the federal government) are permitted to have accounts at the Federal Reserve. These accounts are called reserve accounts. The money balances that depository institutions hold in their reserve accounts are called bank reserves. The money account held by the federal government at the Federal Reserve is called the Treasury General Account. In a sense, a CBDC already exists, but only at the wholesale level and only for a small group of agencies. The question is whether to make it more broadly accessible and, if so, how.

What Is a Central Bank Digital Currency?

Economist David Andolfatto notes that there is more than one model for a central bank digital currency. In this short video, he explains how those models vary and highlights one big difference between a CBDC and traditional bank deposits: how they are insured.

As explained above, the general public already has access to a digital currency in the form of digital deposit liabilities issued by depository institutions. Most households and businesses have checking accounts with private banks. The general public also has access to a central bank liability in the form of physical currency (cash). While banks are obligated to redeem their deposit liabilities for cash on demand, deposits are not legally central bank or government liabilities. To put it another way, CBDC is (or would presumably be made) legal tender, while bank deposits represent claims to legal tender.

Federal Deposit Insurance

Bank accounts in the United States are presently insured up to $250,000 by the Federal Deposit Insurance Corp. From a political-economic point of view, bank deposits at the retail level are a de facto government liability. Moreover, given the role of the Federal Reserve as lender of last resort, one could make a case that large-value bank deposits are also a de facto government liability. To the extent this is so, the legal status of CBDC versus bank money may not be important as far as the ultimate safety of money accounts is concerned.

The Question of Counterparty Risk

Safety is only one of the many concerns surrounding money and payments. There is also the question of how counterparty risk may affect access to funds. For example, even if money in a bank account is insured, access to those funds may be delayed if a bank is suddenly subject to financial stress. This type of risk may be one reason corporate cash managers often turn to the repo market, where deposits are typically collateralized with Treasury securities that can be readily liquidated in the event deposited cash is not returned on time. If there is no restriction on the size of CBDC accounts, the product would effectively provide fully insured money accounts for corporations with no counterparty risk. Such a product, if operated effectively, could very well disintermediate (i.e., eliminate) parts of the money market.

Potential for Efficiency Gains

There is also the question of how a CBDC might improve the overall efficiency of the payments system. This is a difficult question to answer. Proponents often compare a well-designed CBDC with the payments system as it exists today in the United States, which has not caught up to developments in other jurisdictions, including in many developing economies. The U.S. payments system, however, is evolving rapidly to a point that may make CBDC a less attractive proposition. For example, The Clearing House now offers a 24/7 real-time payment services platform . The Federal Reserve’s FedNow platform will provide a similar service.

There may be no single best way to organize a payments system. A payments system is all about processing payment requests and debiting/crediting money accounts. Conceptually, bookkeeping is very simple, even if the actual implementation and operation of a payments system are immensely challenging endeavors. Any arrangement would need mechanisms that guard against fraud. Messaging must be made fast and secure. Institutions (or DAOs) must be trusted to manage the ledgers containing money accounts and related information. Property rights over data ownership would need to be specified and enforced. Some have advocated strongly for a CBDC (e.g., John Crawford et al. in “ FedAccounts: Digital Dollars ,” 2021). Others seem less enthusiastic (e.g., Larry White in “ Should the U.S. Government Create a Token-Based Digital Dollar? ” 2020; George Selgin in “ Central Bank Digital Currency as a Potential Source of Financial Instability ,” 2021; and Christopher Waller in “ CBDC: A Solution in Search of a Problem? ” 2021). In principle, a private, public or private-public arrangement could be made to work well.

What Are the Potential Benefits of a CBDC?

Payments systems have evolved over the years, and a central bank digital currency could be the next step in that evolution. In this short video, economist David Andolfatto examines how a CBDC may increase the efficiency of payments systems. He does so also within the context of The Clearing House’s 24/7 real-time payment services platform.

Like most central banks, the Federal Reserve is designed to facilitate payments at the wholesale level. It performs a vital function and overall performs it well. Traditionally, servicing the needs of a large and demanding retail sector in the United States is left to the private sector. A CBDC could be designed to respect this division of labor in one of two ways:

• Permit free entry into the business of “narrow banking.” This would entail granting Fed master accounts to qualified firms with the requirement that they hold only reserves (and possibly U.S. Treasury bills) as assets. In this arrangement, digital currency remains a private liability (though fully backed by reserves).
• Grant households and firms direct access to CBDC and delegate the responsibility of processing payments at the retail level to private firms. This latter arrangement is the one described in the Federal Reserve Board’s aforementioned report on CBDC. (See box below.)

Central Bank Digital Currency: Read and Comment on the Fed’s Paper

The Federal Reserve Board’s discussion paper (PDF) , released in January 2022, examines the pros and cons of a potential U.S. CBDC. While the Fed has made no decisions on whether to pursue or implement a CBDC, it has been exploring the potential benefits and risks from a variety of angles. As part of this process, the Board is seeking public feedback on whether and how a CBDC could improve an already safe and efficient U.S. domestic payments system. The comment period is open until May 20, 2022.

The ability to write history is a tremendous power. Who should be entrusted with such power? And how should privileges be restricted to ensure honesty, accuracy and (where needed) privacy?

All sorts of individual and group histories play an important role in coordinating economic activity, including credit histories, work histories, performance histories, educational attainment histories and regulatory compliance histories. In this report, we have focused primarily on payment histories in the context of cryptocurrency—including the fact that histories can be fabricated, and that individuals and organizations may be tempted to misrepresent their own histories for private gain at the expense of the broader community. Even relatively well-functioning societies must devote considerable resources to reconciling conflicting claims of past behavior, given the absence of reliable databases that contain those histories. The U.S. Chamber of Commerce Institute for Legal Reform found the cost of litigation in the United States amounted to $429 billion, or 2.3% of U.S. gross domestic product, in 2016. Over 40% of this cost was used to pay legal, insurance and administrative costs. These costs constitute a lower bound, as most disputes are reconciled outside the legal system.

Much of our everyday economic activity occurs outside any formal record-keeping, and societies have relied on informal communal record-keeping to incentivize individual and organizational behavior. Paper and electronic receipts issued for most commercial exchanges are more formal but are often incomplete and easily fabricated. More important records—for physical property, bank accounts, financial assets, licenses, certificates of education, etc.—are managed by trusted authorities.

These traditional forms of record-keeping are likely to be challenged by blockchain technology, which provides a very different model of information management and communication. Competitive pressures compel organizations and institutional arrangements to evolve in response to technological advances in data storage and communications. Consider, for example, how the telegraph, telephone, computer and internet have transformed the way people interact and organize themselves. Advances in blockchain technology are likely to generate even more dramatic changes, though what these may be remains highly uncertain.

• For an accessible introduction to the technology, see Fabian Schär and Aleksander Berentsen’s “ Bitcoin, Blockchain, and Cryptoassets: A Comprehensive Introduction ,” MIT Press, 2020.
• See Narayana Kocherlakota’s “ The Technological Role of Fiat Money ,” Federal Reserve Bank of Minneapolis, Quarterly Review , 1998.
• Relatively minor patches to the code to fix bugs or otherwise improve performance have been implemented. But certain key parameters, like the one that governs the cap on the supply of bitcoin, are likely impervious to change.
• Beyond viewing the balances, one can also view the transaction histories of every monetary unit in the account (i.e., its movement from account to account over time since it was created).
• It is important to note that many cryptocurrency users hold their funds via third parties to whom they relinquish control of their private keys. If an intermediary is hacked and burgled, one’s cryptocurrency holdings may be stolen. This has nothing to do with security flaws in the cryptocurrency itself—but with the security flaws of the intermediary.
• See David Andolfatto and Andrew Spewak’s “ Whither the Price of Bitcoin? ” Federal Reserve Bank of St. Louis, Economic Synopses , 2019.
• Legal tender is an object that creditors cannot legally refuse as payment for debt. While deposits are claims to legal tender (they can be converted into cash on demand), they also constitute claims against all bank assets in the event of bankruptcy.
• For a more extensive review, see Fabian Schär’s “ Decentralized Finance: On Blockchain- and Smart Contract-Based Financial Markets ,” Federal Reserve Bank of St. Louis, Review , 2021; also see an analysis by Sara Feenan et al. in “ Decentralized Financial Market Infrastructures: Evolution from Intermediated Structures to Decentralized Structures for Financial Agreements ,” The Journal of FinTech , 2021.
• See Nick Szabo’s “ Smart Contracts ” (1994) and “ The Idea of Smart Contracts ” (1997). The key idea is that contractual terms, once agreed upon, are not renegotiable and are therefore automatically executed in the future. In economic theory, so-called Arrow-Debreu securities have the same property.
• For example, Hyperledger allows for confidential transactions, whereas Ethereum, a public network, does not. Bitcoin is also able to handle a variety of smart contracts.
• Some stablecoins stabilize their value by pegging to the U.S. dollar, backed with non-U.S. dollar assets; Dai, for example, pegs its value to a senior tranche of other cryptoassets. See Dankrad Feist’s “ On Supply and Demand for Stablecoins ,” 2021.
• The opacity of financial structures is not necessary to explain bank runs. For example, the canonical model of bank runs assumes the existence of transparent balance sheets. See Douglas Diamond and Philip Dybvig’s “ Bank Runs, Deposit Insurance, and Liquidity ,” The Journal of Political Economy , 1983.
• The U.S. Chamber of Commerce Institute for Legal Reform found the cost of litigation in the United States amounted to $429 billion, or 2.3% of U.S. gross domestic product, in 2016. Over 40% of this cost was used to pay legal, insurance and administrative costs. These costs constitute a lower bound, as most disputes are reconciled outside the legal system.

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An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends

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• Published: 04 July 2019

A systematic review of blockchain

• Min Xu   ORCID: orcid.org/0000-0002-3929-7759 1 ,
• Xingtong Chen 1 &
• Gang Kou 1  

Financial Innovation volume  5 , Article number:  27 ( 2019 ) Cite this article

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Blockchain is considered by many to be a disruptive core technology. Although many researchers have realized the importance of blockchain, the research of blockchain is still in its infancy. Consequently, this study reviews the current academic research on blockchain, especially in the subject area of business and economics. Based on a systematic review of the literature retrieved from the Web of Science service, we explore the top-cited articles, most productive countries, and most common keywords. Additionally, we conduct a clustering analysis and identify the following five research themes: “economic benefit,” “blockchain technology,” “initial coin offerings,” “fintech revolution,” and “sharing economy.” Recommendations on future research directions and practical applications are also provided in this paper.

Introduction

The concepts of bitcoin and blockchain were first proposed in 2008 by someone using the pseudonym Satoshi Nakamoto, who described how cryptology and an open distributed ledger can be combined into a digital currency application (Nakamoto 2008 ). At first, the extremely high volatility of bitcoin and the attitudes of many countries toward its complexity restrained its development somewhat, but the advantages of blockchain—which is bitcoin’s underlying technology—attracted increasing attention. Some of the advantages of blockchain include its distributed ledger, decentralization, information transparency, tamper-proof construction, and openness. The evolution of blockchain has been a progressive process. Blockchain is currently delimited to Blockchain 1.0, 2.0, and 3.0, based on their applications. We provide more details on the three generations of blockchain in the Appendix . The application of blockchain technology has extended from digital currency and into finance, and it has even gradually extended into health care, supply chain management, market monitoring, smart energy, and copyright protection (Engelhardt 2017 ; Hyvarinen et al. 2017 ; Kim and Laskowski 2018 ; O'Dair and Beaven 2017 ; Radanovic and Likic 2018 ; Savelyev 2018 ).

Blockchain technology has been studied by a wide variety of academic disciplines. For example, some researchers have studied the underlying technology of blockchain, such as distributed storage, peer-to-peer networking, cryptography, smart contracts, and consensus algorithms (Christidis and Devetsikiotis 2016 ; Cruz et al. 2018 ; Kraft 2016 ). Meanwhile, legal researchers are interested in the regulations and laws governing blockchain-related technology (Kiviat 2015 ; Paech 2017 ). As the old saying goes: scholars in different disciplines have many different analytical perspectives and “speak many different languages.” This paper focuses on analyzing and combing papers in the field of business and economics. We aim to identify the key nodes (e.g., the most influential articles and journals) in the related research and to find the main research themes of blockchain in our discipline. In addition, we hope to offer some recommendations for future research and provide some suggestions for businesses that wish to apply blockchain in practice.

This study will conduct a systematic and objective review that is based on data statistics and analysis. We first describe the overall number and discipline distribution of blockchain-related papers. A total of 756 journal articles were retrieved. Subsequently, we refined the subject area to business and economics, and were able to add 119 articles to our further analysis. We then explored the influential countries, journals, articles, and most common keywords. On the basis of a scientific literature analysis tool, we were able to identify five research themes on blockchain. We believe that this data-driven literature review will be able to more objectively present the status of this research.

The rest of this paper is organized as follows. In the next section, we provided an overview of the existing articles in all of the disciplines. We holistically describe the number of papers related to blockchain and discipline distribution of the literature. We then conduct a further analysis in the subject field of business and economics, where we analyze the countries, publications, highly cited papers, and so on. We also point out the main research themes of this paper, based on CiteSpace. This is followed by recommendations for promising research directions and practical applications. In the last section, we discuss the conclusions and limitations.

Overview of the current research

In our research, we first conducted a search on Web of Science Core Collection (WOS), including four online databases: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Arts & Humanities Citation Index (A&HCI), and Emerging Sources Citation Index (ESCI). We chose WOS because the papers in these databases can typically reflect scholarly attention towards blockchain. When searching the term “blockchain” as a topic, we found a total of 925 records in these databases. After filtering out the less representative record types, we reduced these papers to 756 articles that were then used for further analysis. We extracted the full bibliographic record of the articles that we identified from WOS, including information on the title, author, keywords, abstract, journal, year, and other publication information. These records were then exported to CiteSpace for subsequent analysis. CiteSpace is a scientific literature analysis tool that enables us to visualize trends and patterns in the scientific literature (Chen 2004 ). In this paper, CiteSpace is used to visually represent complex structures for statistical analysis and to conduct cluster analysis.

Table  1 shows the number of academic papers published per year. We have listed the number of all of the publications in WOS, the number of articles in all of the disciplines, and the number of articles in business and economics subjects. It should be noted that we retrieved the literature on March 25, 2019. Therefore, the number of articles in 2019 is relatively small. The number of papers has continued to grow in recent years, which suggests that there is a growing interest in blockchain. All of the extracted papers in WOS were published after 2015, which is seven years after blockchain and bitcoin was first described by Nakamoto. In these initial seven years, many papers were published online or indexed by other databases. However, we have not discussed these papers here. We only chose WOS, representative high-level literature databases. This is the most common way of doing a literature review (Ipek 2019 ).

In the 756 articles that we managed to retrieve, the three most common keywords besides blockchain are bitcoin, smart contract, and cryptocurrency, with the frequency of 113 times, 72 times, and 61 times, respectively. This shows that the majority of the literature mentions the core technology of blockchain and its most widely known application—bitcoin.

In WOS, each article is assigned to one or more subject categories. Therefore, we use CiteSpace to visualize what research areas are involved in current research on blockchain. Figure  1 shows a network of such subject categories. The most common category is Computer Science, which has the largest circle, followed by Engineering and Telecommunications. Business and Economics is also a common subject area for blockchain. Consequently, in the following session, we will conduct further analysis in this field.

Disciplines in blockchain

Articles in business and economics

Given that the main objective of our research was to understand the research of blockchain in the area of economics and management, we conduct an in-depth analysis on the papers in this field. We refined the research area to Business and Economics, and we finally retrieved 119 articles from WOS. In this session, we analyzed their published journals, research topics, citations, and so on, to depict the research status of blockchain in the field of business and economics more comprehensively.

There are several review papers on blockchain. Each of these paper contains a summary of multiple research topics, instead of a single topic. We do not include these literature reviews in our paper. However, it is undeniable that these articles also play an important role on the study of blockchain. For instance, Wang et al. ( 2019 ) investigate the influence of blockchain on supply chain practices and policies. Zhao et al. ( 2016 ) suggest blockchain will widely adopted in finance and lead to many business innovations and research opportunities.

The United States, the United Kingdom, and Germany are the top three countries by the number of papers published on blockchain; the specific data are shown in Table  2 . The United States released more papers than the other countries and it produced more than one-third of the total articles. As of the time of data collection, China contributed 11 papers, ranking fourth. The 119 papers in total are drawn from 17 countries and regions. In contrast, we searched “big data” and “financial technology” in the same way, and found 286 papers on big data that came from 24 countries, while 779 papers on fintech came from 43 countries. This shows that blockchain is still an emerging research field, and it needs more countries and scholars to join in the research effort.

We counted the journals published in these papers and we found that 44 journals published related papers. Table  3 lists the top 11 journals to have published blockchain research. First is “Strategic Change: Briefings in Entrepreneurial Finance,” followed by “Financial Innovation” and “Asia Pacific Journal of Innovation and Entrepreneurship.” The majority of papers in the journal “Strategic Change” were published in 2017, except for one in 2018 and one in 2019. Papers in the journal “Financial Innovation” were generally published in 2016, with one published in 2017 and one in 2019. All five of the papers in the journal “Asia Pacific Journal of Innovation and Entrepreneurship” were published in 2017.

Cited references

Table  4 presents the top six cited publications, which were cited no less than five times. The list consists of three books and three journal articles. Some of these publications introduce blockchain from a technical perspective and some from an application perspective. Swan’s ( 2015 ) book illustrates the application scenarios of blockchain technology. In this book, the author describes that blockchain is essentially a public ledger with potential as a decentralized digital repository of all assets—not only tangible assets but also intangible assets such as votes, software, health data, and ideas. Tapscott and Tapscott’s ( 2016 ) book explains why blockchain technology will fundamentally change the world. Yermack ( 2017 ) points out that blockchain will have a huge impact and will present many challenges to corporate governance. Böhme et al. ( 2015 ) introduce bitcoin, the first and most famous application of blockchain. Narayanan et al. ( 2016 ) also focus on bitcoin and explain how bitcoin works at a technical level. Lansiti and Lakhani ( 2017 ) argue it will take years to truly transform the blockchain because it is a fundamental rather than destructive technology, which will not drive implementation, and companies will need other incentives to adopt blockchain.

Most influential articles

These 119 papers were cited 314 times in total, and 270 times without self-citations. The number of articles that they cited are 221, of which 197 are non-self-citations. The most influential articles with more than 10 citations are listed in Table  5 . The most popular article in our dataset is Lansiti and Lakhani ( 2017 ), with 49 citations in WOS. This suggests that this article has had a strong influence on the research of blockchain. This paper believes there is still a distance to the real application of the blockchain. The other articles describe how blockchain affects and works in various areas, such as financial services, organizational management, and health care. Since blockchain is an emerging technology, it is particularly necessary to explore how to combine blockchains with various industries and fields.

By comparing the journals in Tables 4 and 5 , we find that some journals appeared in both of the lists, such as Financial Innovation. In other words, papers on blockchain are more welcomed in these journals and the journal’s papers are highly recognized by other scholars. Meanwhile, although journals such as Harvard Business Review have only published a few papers related to blockchain, they are highly cited. Consequently, the journals in both of these lists are of great importance.

Research themes

Addressing research themes is crucial to understanding a research field and exploring future research directions. This paper explored the research topic based on keywords. Keywords are representative and concise descriptions of article content. First, we analyzed the most common keywords used by the papers. We find that the top five most frequently used keywords are “blockchain,” “bitcoin,” “cryptocurrency,” “fintech,” and “smart contract.” Although the potential for blockchain applications goes way beyond digital currencies, bitcoin and other cryptocurrencies—as an important blockchain application scenario in the finance industry—were widely discussed in these articles. Smart contracts allow firms to set up automated transactions in blockchains, thus playing a fundamentally supporting role in blockchain applications. Similar to the literature in all of the subject areas, studies in business and economics also frequently use bitcoin, cryptocurrency, and smart contract as their keywords. The difference is that many researchers have combined blockchain with finance, regarding it as an important financial technology.

After analyzing the frequency of keywords, we conducted a keywords clustering analysis to identify the research themes. As shown in Fig.  2 , five clusters were identified through the log-likelihood ratio (LLR) algorithm in Citespace, they are: cluster #0 “economic benefit,” cluster #1 “blockchain technology,” cluster #2 “initial coin offerings,” cluster #3 “fintech revolution,” and cluster #4 “sharing economy.”

Disciplines and topics

Many researchers have studied the economic benefits of blockchain. They suggest the application of blockchain technology to streamline transactions and settlement processes can effectively reduce the costs associated with manual operations. For instance, in the health care sector, blockchain can play an important role in centralizing research data, avoiding prescription drug fraud, and reducing administrative overheads (Engelhardt 2017 ). In the music industry, blockchain could improve the accuracy and availability of copyright data and significantly improve the transparency of the value chain (O'Dair and Beaven 2017 ). Swan ( 2017 ) expound the economic value of block chain through four typical applications, such as digital asset registries, leapfrog technology, long-tail personalized economic services, and payment channels and peer banking services.

The representative paper for cluster “blockchain technology” was published by Lansiti and Lakhani ( 2017 ), who analyze the inherent features of blockchain and pointed out that we still have a lot to do to apply blockchain extensively. Other researchers have explored the characteristics of blockchain technology from multiple perspectives. For example, Xu ( 2016 ) explores the types of fraud and malicious activities that blockchain technology can prevent and identifies attacks to which blockchain remains vulnerable. Meanwhile, Aune et al. ( 2017 ) propose a cryptographic approach to solve information leakage problems on a blockchain.

Initial coin offering (ICO) is also a research topic of great concern to scholars. Many researchers analyze the determinants of the success of initial coin offerings (Adhami et al. 2018 ; Ante et al. 2018 ). For example, Fisch ( 2019 ) assesses the determinants of the amount raised in ICOs and discusses the role of signaling ventures’ technological capabilities in ICOs. Deng et al. ( 2018 ) argue the outright ban on ICOs might hamper revolutionary technological development and they provided some regulatory reform suggestions on the current ICO ban in China.

Many researchers have explored blockchain’s support for various industries. The fintech revolution brought by the blockchain has received extensive attention (Yang and Li 2018 ). Researchers agree that this nascent technology may transform traditional trading methods and practice in financial industry (Ashta and Biot-Paquerot 2018 ; Chen et al. 2017 ; Kim and Sarin 2018 ). For instance, Gomber et al. ( 2018 ) discuss transformations in four areas of financial services: operations management, payments, lending, and deposit services. Dierksmeier and Seele ( 2018 ) address the impact of blockchain technology on the nature of financial transactions from a business ethics perspective.

Another cluster corresponds to the sharing economy. A handful of researchers have focused on this field and they have discussed the supporting role played by blockchain in the sharing economy. Pazaitis et al. ( 2017 ) describe a conceptual economic model of blockchain-based decentralized cooperation that might better support the dynamics of social sharing. Sun et al. ( 2016 ) discuss the contribution of emerging blockchain technologies to the three major factors of the sharing economy (i.e., human, technology, and organization). They also analyze how blockchain-based sharing services contribute to smart cities.

In this section, we will discuss the following issues: (1) What will be the future research directions for blockchain? (2) How can businesses benefit from blockchain? We hope that our discussions will be able to provide guidance for future academic development and social practice.

What will be the future research directions for blockchain?

In view of the five themes mentioned in this paper, we provide some recommendations for future research in this section.

The economic benefits of blockchain have been extensively studied in previous research. For individual businesses, it is important to understand the effects of blockchain applications on the organizational structure, mode of operation, and management model of the business. For the market as a whole, it is important to determine whether blockchain can resolve the market failures that are brought about by information asymmetry, and whether it can increase market efficiency and social welfare. However, understanding the mechanisms through which blockchain influences corporate and market efficiency will require further academic inquiry.

For researchers of blockchain technology, this paper suggests that we should pay more attention to privacy protection and security issues. Despite the fact that all of the blockchain transactions are anonymous and encrypted, there is still a risk of the data being hacked. In the security sector, there is a view that absolute security can never be guaranteed wherever physical contact exists. Consequently, the question of how to share transaction data while also protecting personal data privacy are particularly vital issues for both academic and social practice.

Initial coin offering and cryptocurrency markets have grown rapidly. They bring many interesting questions, such as how to manage digital currencies. Although the majority of the previous research has focused on the determinants of success of initial coin offerings, we believe that future research will discuss how to regulate cryptocurrency and the ICO market. The success of blockchain technology in digital currency applications prior to 2015 caught the attention of many traditional financial institutions. As blockchain has continued to reinvent itself, in 2019 it is now more than capable of meeting the needs of the finance industry. We believe that blockchain is able to achieve large-scale applications in many areas of finance, such as banking, capital markets, Internet finance, and related fields. The deep integration of blockchain technology and fintech will continue to be a promising research direction.

The sharing economy is often defined as a peer-to-peer based activity of sharing goods and services among individuals. In the future, sharing among enterprises may become an important part of the new sharing economy. Consequently, building the interconnection of blockchains may become a distinct trend. These interconnections will facilitate the linkages between processes of identity authentication, supply chain management, and payments in commercial operations. They will also allow for instantaneous information exchange and data coordination among enterprises and industries.

How can businesses benefit from blockchain?

Businesses can leverage blockchains in a variety of ways to gain an advantage over their competitors. They can streamline their core business, reduce transaction costs, and make intellectual property ownership and payments more transparent and automated (Felin and Lakhani 2018 ). Many researchers have discussed the application of blockchain in business. After analyzing these studies, we believe that enterprises can consider applying blockchain technology in the four aspects that follow.

Accounting settlement and crowdfunding

Bitcoin or another virtual currency supported by blockchain technology can help businesses to solve funding-related problems. For instance, cryptocurrencies support companies who wish to implement non-cash payments and accounting settlement. The automation of electronic transaction management accounting improves the level of control of monetary business execution, both internally and externally (Zadorozhnyi et al. 2018 ). In addition, blockchain technology represents an emerging source of venture capital crowdfunding (O'Dair and Owen 2019 ). Investors or founders of enterprises can obtain alternative entrepreneurial finance through token sales or initial coin offerings. Companies can handle financial-related issues more flexibly by holding, transferring, and issuing digital currencies that are based on blockchain technology.

Data storage and sharing

As the most valuable resource, data plays a vital role in every enterprise. Blockchain provide a reliable storage and efficient use of data (Novikov et al. 2018 ). As a decentralized and secure ledger, blockchain can be used to manage digital asset for many kinds of companies (Dutra et al. 2018 ). Decentralized data storage means you do not give the data to a centralized agency but give it instead to people around the world because no one can tamper with the data on the blockchain. Businesses can use blockchain to store data, improve the transparency and security of the data, and prevent the data from being tampered with. At the same time, blockchain also supports data sharing. For instance, all of the key parties in the accounting profession leverage an accountancy blockchain to aggregate and share instances of practitioner misconduct across the country on a nearly real-time basis (Sheldon 2018 ).

Supply chain management

Blockchain technology has the potential to significantly change supply chain management (SCM) (Treiblmaier 2018 ). Recent adoptions of the Internet of Things and blockchain technologies support better supply-chain provenance (Kim and Laskowski 2018 ). When the product goes from the manufacturer to the customer, important data are recorded in the blockchain. Companies can trace products and raw materials to effectively monitor product quality.

Smart trading

Businesses can build smart contracts on blockchain, which is widely used to implement business collaborations in general and inter-organizational business processes in particular. Enterprises can automate transactions based on smart contracts on block chains without manual confirmation. For instance, businesses can file taxes automatically under smart contracts (Vishnevsky and Chekina 2018 ).

Conclusions

This paper reviews 756 articles related to blockchain on the Web of Science Core Collection. It shows that the most common subject area is Computer Science, followed by Engineering, Telecommunications, and Business and Economics. In the research of Business and Economics, several key nodes are identified in the literature, such as the top-cited articles, most productive countries, and most common keywords. After a cluster analysis of the keywords, we identified the five most popular research themes: “economic benefit,” “blockchain technology,” “initial coin offerings,” “fintech revolution,” and “sharing economy.”

As an important emerging technology, blockchain will play a role in many fields. Therefore, we believe that the issues related to commercial applications of blockchain are critical for both academic and social practice. We propose several promising research directions. The first important research direction is understanding the mechanisms through which blockchain influences corporate and market efficiency. The second potential research direction is privacy protection and security issues. The third relates to how to manage digital currencies and how to regulate the cryptocurrency market. The fourth potential research direction is how to deeply integrate blockchain technology and fintech. The final topic is cross-chain technology—if each industry has its own blockchain system, then researchers and developers must discover new ways to exchange data. This is the key to achieving the Internet of Value. Thus, cross-chain technology will become an increasingly important topic as time goes on.

Businesses can benefit considerably from blockchain technology. Therefore, we suggest that the application of blockchain be taken into consideration when businesses have the following requirements: accounting settlement and crowdfunding, data storage and sharing, supply chain management, and smart trading.

Our study has recognized some limitations. First, this paper only analyzes the literature in Web of Science Core Collection databases (WOS), which may lead to the incompleteness of the relevant literature. Second, we filter our literature base on the subject category in WOS. In this process, we may have omitted some relevant research. Third, our recommendations have subjective limitations. We hope to initiate more research and discussions to address these points in the future.

Availability of data and materials

Data used in this paper were collected from Web of Science Core Collection.

Abbreviations

Initial coin offering

Web of Science Core Collection

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Acknowledgements

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This research is supported by grants from National Natural Science Foundation of China (Nos. 71701168 and 71701034).

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Three generations of blockchain

The scope of blockchain applications has increased from virtual currencies to financial applications to the entire social realm. Based on its applications, blockchain is delimited to Blockchain 1.0, 2.0, and 3.0.

Blockchain 1.0

Blockchain 1.0 was related to virtual currencies, such as bitcoin, which was not only the first and most widely used digital currency but it was also the first application of blockchain technology (Mainelli and Smith 2015 ). Digital currencies can reduce many of the costs associated with traditional physical currencies, such as the costs of circulation. Blockchain 1.0 produced a great many applications, one of which was Bitcoin. Most of these applications were digital currencies and tended to be used commercially for small-value payments, foreign exchange, gambling, and money laundering. At this stage, blockchain technology was generally used as a cryptocurrency and for payment systems that relied on cryptocurrency ecosystems.

Blockchain 2.0

Broadly speaking, Blockchain 2.0 includes Bitcoin 2.0, smart-contracts, smart-property, decentralized applications (Dapps), decentralized autonomous organizations (DAOs), and decentralized autonomous corporations (DACs) (Swan 2015 ). However, most people understand Blockchain 2.0 as applications in other areas of finance, where it is mainly used in securities trading, supply chain finance, banking instruments, payment clearing, anti-counterfeiting, establishing credit systems, and mutual insurance. The financial sector requires high levels of security and data integrity, and thus blockchain applications have some inherent advantages. The greatest contribution of Blockchain 2.0 was the idea of using smart-contracts to disrupt traditional currency and payment systems. Recently, the integration of blockchain and smart contract technology has become a popular research topic in problem resolution. For example, Ethereum, Codius, and Hyperledger have established programmable contract language and executable infrastructure to implement smart contracts.

Blockchain 3.0

In ‘Blockchain: Blueprint for a New Economy’, Blockchain 3.0 is described as the application of blockchain in areas other than currency and finance, such as in government, health, science, culture, and the arts (Swan 2015 ). Blockchain 3.0 aims to popularize the technology, and it focuses on the regulation and governance of its decentralization in society. The scope of this type of blockchain and its potential applications suggests that blockchain technology is a moving target (Crosby et al. 2016 ). Blockchain 3.0 envisions a more advanced form of “smart contracts” to establish a distributed organizational unit that makes and is subject to its own laws and which operates with a high degree of autonomy (Pieroni et al. 2018 ).

The integration of blockchain with tokens is an important combination of Blockchain 3.0. Tokens are proofs of digital rights, and blockchain tokens are widely recognized thanks to Ethereum and its ERC20 standard. Based on this standard, anyone can issue a custom token on Ethereum and this token can represent any right or value. Tokens refer to economic activities generated through the creation of encrypted tokens, which are principally but not exclusively based on the ERC20 standard. Tokens can serve as a form of validation of any right, including personal identity, academic diplomas, currency, receipts, keys, event tickets, rebate points, coupons, stocks, and bonds. Consequently, tokens can validate virtually any right that exists within a society. Blockchain is the back-end technology of the new era, while tokens are its front-end economic face. The combination of the two will bring about major societal transformation. Meanwhile, Blockchain 3.0 and its token economy continue to evolve.

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Xu, M., Chen, X. & Kou, G. A systematic review of blockchain. Financ Innov 5 , 27 (2019). https://doi.org/10.1186/s40854-019-0147-z

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Review article, a review on blockchain technology and blockchain projects fostering open science.

• 1 Department of Business and Industrial Engineering, Offenburg University of Applied Sciences, Offenburg, Germany
• 2 Department of Mathematics, FIZ Karlsruhe - Leibnitz-Institute for Information Infrastructure, Berlin, Germany
• 3 School of Electrical, Information and Media Engineering, University of Wuppertal, Wuppertal, Germany

Many sectors, like finance, medicine, manufacturing, and education, use blockchain applications to profit from the unique bundle of characteristics of this technology. Blockchain technology (BT) promises benefits in trustability, collaboration, organization, identification, credibility, and transparency. In this paper, we conduct an analysis in which we show how open science can benefit from this technology and its properties. For this, we determined the requirements of an open science ecosystem and compared them with the characteristics of BT to prove that the technology suits as an infrastructure. We also review literature and promising blockchain-based projects for open science to describe the current research situation. To this end, we examine the projects in particular for their relevance and contribution to open science and categorize them afterwards according to their primary purpose. Several of them already provide functionalities that can have a positive impact on current research workflows. So, BT offers promising possibilities for its use in science, but why is it then not used on a large-scale in that area? To answer this question, we point out various shortcomings, challenges, unanswered questions, and research potentials that we found in the literature and identified during our analysis. These topics shall serve as starting points for future research to foster the BT for open science and beyond, especially in the long-term.

1. Introduction

The blockchain technology (BT) offers great potential to foster various sectors ( Casino et al., 2018 ) with its unique combination of characteristics, for example, decentralization, immutability, and transparency. We see promising possibilities in the use of this technology for science and academia. In this paper, we want to show why the BT suits especially to open science. So far, the most prominent attention the technology received was through news from industry and media ( Morini, 2016 ; Notheisen et al., 2017 ; Carson et al., 2018 ; Volpicelli, 2018 ) about the development of cryptocurrencies. Examples are Bitcoin, Litecoin, Dash, and Monero, which all are having remarkable market capitalizations 1 . BT, however, is not limited to cryptocurrencies. There are already existing blockchain-based applications in industry and the public sector like crowdfunding ( Conley, 2017 ; Li and Mann, 2018 ; Arnold et al., 2019 ), tracking of goods in supply chains ( Abeyratne and Monfared, 2016 ; Tian, 2016 ; Hepp et al., 2018 ), authentication ( Cruz et al., 2018 ; Ihle and Sanchez, 2018 ), and voting services ( Swan, 2015a ; Osgood, 2016 ); many more are under development ( Brandon, 2016 ; Davidson et al., 2016 ; Fanning and Centers, 2016 ; Nguyen, 2016 ; Scott, 2016 ). The Fraunhofer Institute for Scientific and Technical Trend Analysis (INT) in Germany published a study ( Schütte et al., 2018 ) showing that currently BT can be most frequently found in applications used in the financial sector.

The typical use case in that area for BT is the exchange of value units without the need of intermediaries ( Nakamoto, 2008 ; Ben-Sasson et al., 2014 ). Examples for that are the already mentioned cryptocurrencies and other applications that, for instance, allowing individuals to offer and sell their digital assets like art or data from sensors on a marketplace ( Draskovic and Saleh, 2017 ), or enabling property owners to transfer their land without a notary ( Kombe et al., 2017 ). The pioneering role of the financial sector seems obvious because cryptocurrencies were the first usable blockchain applications. Nevertheless, the potential of this technology has attracted the attention of other areas in recent years, leading to a vast number of new projects 2 . BT is still in an early development phase without widely adopted standardization and frameworks yet.

There are already some scientific sources (but far more gray literature) on how the BT can be used to mitigate existing problems in science like the reproducibility of results from published articles and experiments. Due to immutability, append-only function, and a viewable record of all transactions, BT can provide transparency for all users over every step done in a system. As a result of that, an environment gets created that does not need a trusted authority because malicious behavior is technically difficult. The decentralization enables researchers to build their own open ecosystem for research data, metadata, and communication that follows the philosophy of open science. For us, open science is characterized above all by the fact that everyone can openly participate, collaborate, and contribute to science. The results of these activities, such as research data, processes, studies, and methods, are freely available so that they can be reused and reproduced. In section 3, we go into open science and its definitions in more detail.

Besides reproducibility of experiments ( Prinz et al., 2011 ; Collins and Tabak, 2014 ; Gilbert et al., 2016 ; Furlanello et al., 2017 ), BT can also get used to address several other scientific problems ( Gipp et al., 2015 , 2017 ; Anonymous, 2016 ; Dhillon, 2016 ; Golem, 2016 ; Wolf et al., 2016 ; Breitinger and Gipp, 2017 ; van Rossum, 2017 ; Androulaki et al., 2018 ; Bartling, 2018 ; Janowicz et al., 2018 ) like trust problems in the form of malicious behavior in peer-review processes ( Stahel and Moore, 2014 ; Degen, 2016 ; Dansinger, 2017 ), lacking quality and redundancy of study designs ( Macleod et al., 2014 ; Belluz and Hoffman, 2015 ), and the restriction of free access to scientific publications ( Myllylahti, 2014 ; Teplitskiy et al., 2017 ; Schiltz, 2018 ). BT also has the ability to increase the trustability of studies and collaborations among researchers in complex science projects by the use of its characteristics.

BT stands out from other systems in its exceptional technical architecture, which allows the technology to get adapted for a variety of use cases. For example, developers have the possibility to design blockchains for open or private access combined with individual governance models depending on its purpose. In addition to the technical perspective, cryptocurrencies, for example, provide additional, unique opportunities to create business models and incentives for users or entire communities. However, besides BT, there are also other technologies that are applicable to open science. One example is the peer-to-peer data synchronization protocol Dat ( Ogden et al., 2018 ) that also supports immutable and decentralized storage and can be used as an infrastructure for scholarly communication ( Hartgerink, 2019 ). The protocol got inspired by several existing systems, one of them being BitTorrent ( Pouwelse et al., 2005 ). Further non-blockchain-based approaches supporting open science include the research and collaboration platforms Open Science Framework (OSF) ( OSF, 2019 ) and OPERAS ( Mounier et al., 2018 ), the open access repository Zenodo ( Zenodo, 2019 ), the research data infrastructure offered by the European Science Cloud (EOSC) ( EOSC, 2019 ), and the publishing platform F1000Research ( F1000 , 2019 ).

We want to point out at an early stage of this paper that BT is just a technology and certainly not the silver bullet that will overcome all problems we are facing in science today. Some of the issues cannot get solved by technology alone, instead require the involved persons to rethink habits, behaviors, and processes. In some cases, it might even lead to researchers having to renounce privileges. There is also criticism of the use of BT for science. Hartgerink (2018) argues that blockchains can even amplify inequalities by increasing artificial scarcity and relying on free market principles. Another point of criticism affects the consensus principle as the fundamental definition of truth in a blockchain. Firstly, there is always a chance of hijacking a blockchain with a so-called 51%-attack. Secondly, and more relevant from a philosophical point of view, Hartgerink asks whether we need a consensus for scientific theories or ideas at all.

Overall, our work contributes to understanding the BT and the possibilities it offers to design, implement, and improve open science projects and applications across all different scientific fields. We think it is a suitable technology to support the transformation of open science. The motivation for this work lies in the circumstance that there is currently no systematic review of the general suitability of BT for open science, the state of the art or related vital challenges and research potentials. We are addressing these topics in this paper.

The BT is, besides the financial area, also emerging in many other sectors and gets continuously more popular. It is difficult to overview the market of existing and planned projects since there is no holistic public database or repository for it. Further, the range of visions, concepts, and prototypes is constantly increasing, which means that this review can only provide a snapshot and does not claim to be complete or exhaustive.

We conducted a systematic review of the research topic by first searching for relevant literature. It has turned out that this topic is quite novel, and there are just a few publications about how BT can be used to foster open science or science in general. In a literature review about the usage of BT in different domains ( Casino et al., 2018 ), the application field of science did not even get mentioned as an application domain. Besides literature, we also focused our analysis on various blockchain projects that can foster open science in different ways. We want to provide a transparent and reproducible review, thus in the following, we describe our research questions and methodology.

1. What are the current requirements for a technical open science infrastructure, and how do they compare with BT features?

2. What is the current status and perspectives for the use of BT in science and academia?

3. What are the biggest challenges and obstacles that are preventing successful implementation and adoption of BT as supporting infrastructure for open science?

(1) We approached this question by comparing the characteristics of BT with the goals and needs of open science. We examined whether it is able to deliver a reasonable and adequate fundament for an open science ecosystem. At first, we studied existing literature to describe what open science is (section 3.1), what it aims to be, and what the requirements for such an infrastructure (section 3.2) are. Then, we examined the BT to understand how it works and what characteristics it has (section 4.1). Finally, we created a matrix that shows all related infrastructure requirements and compares them to the characteristics of the BT to determine how they match and whether they can be fulfilled (section 4.2).

(2) To answer the second research question, we discussed relevant literature, gray literature, and projects that we found, collected, and screened from different search engines and reference lists until April 2019. Primarily, we used Google Scholar 3 , PLOS 4 , CiteSeerX 5 , Microsoft Academic Search 6 , and GitHub as file hoster of software development projects. Secondarily, we examined research publications, whitepapers, and blogs. We found the most relevant literature and projects by using the search terms “blockchain” with “science,” “publishing,” “peer review,” and “reproducibility.” The relevance of literature was made sure by reading their abstracts and, partially, the whole work if the abstract was not clear enough to rate the specific content. If a paper had no meaningful content for our research, we excluded it from our review. From there on, we screened the reference lists of the remaining literature to find further suitable sources, known as snowballing. After that, we made a full-text review of the content of all papers to get an overview of the current research state that showed the potential and increasing interest in the BT for open science (section 5.2).

Besides the literature, we also collected exciting and promising blockchain-based projects consisting of concepts, prototypes, and already deployed applications. We found in numbers many more projects than relevant scientific publications. The majority of the projects got identified in the reviewed literature and the rest through search engines. These projects are either designed specifically for open science, or some of their functionalities are usable in that area. We also found some very early concepts and ideas that only exist in forums or social media networks. However, their potential is not ratable yet due to low progress and information scarcity, so we did not include them into detailed analysis. Altogether, we collected and analyzed 83 projects but removed 23 of them early due to cancelation, irrelevancy, or inactivity (no actions or news for more than 1 year), leaving 60 projects left. We summarized and mapped these into different categories according to their use and created an overview of our approach (section 5.1). The so built structure and the review of projects help to gain a better understanding of the current situation of research in this area (section 5.3). Finally, we made a summary and discussed our findings (section 5.4). For a complete overview, we created a database (see Supplementary Material ) containing a short description, project state, and other characteristics for each project.

(3) As a basis to process the third research question, we used the knowledge gained from answering the first and second research question, and the analysis of literature and projects. First, we conducted a brainstorming, discussed all mentioned topics, and rated them each individually. Then we created a ranking of the topics by collecting and evaluating the ratings of all people who were involved in the brainstorming. Finally, we took the issues of rank one to five and described them in terms of current challenges, research potentials, and open questions that should be addressed to foster the BT for open science (sections 6.1–6.5).

3. Open Science

In this section, we briefly describe the philosophy behind open science and existing problems in science it can mitigate (section 3.1). Furthermore, we did an analysis to point out what requirements have to be met to establish a technical ecosystem that follows and lives the principles of open science (section 3.2). Finally, we created an overview of the requirements we determined in this section.

3.1. Overview

There are several definitions of what open science is, but there is not a universal definition that is generally valid. We think the definition of FOSTER 7 is a good representation of the term: “Open Science is the practice of science in such a way that others can collaborate and contribute, where research data, lab notes and other research processes are freely available, under terms that enable reuse, redistribution and reproduction of the research and its underlying data and methods.” There are other descriptions such as the “open” definition 8 and one from the OECD 9 . An illustrated story about the development of open science can be viewed here ( Green, 2017 ). Overall, open science is an umbrella term for a multitude of assumptions about how the future of knowledge creation and dissemination (also education) will work ( Fecher and Friesike, 2014 ). There are different types of implementations, such as sharing of computing and storage resources in an open science grid (OSG) ( Pordes et al., 2007 ; Altunay et al., 2011 ) or open access repositories for research literature as SocArXiv 10 , CiteSeerX, and arXiv 11 . We want to briefly discuss open science in its chances and challenges to provide a common point of definition from that we will link the possibilities of BT to the fundamental concept of open science. Fecher and Friesike (2014) structured open science in five schools of thought and Tennant et al. (2019) expanded them by a sixth (see Table 1 ). It summarizes the identified schools with their central assumptions, their goals, and keywords.

Table 1 . Six open science schools of thought. The sources ( Fecher and Friesike, 2014 ; Tennant et al., 2019 ) got combined.

As we have learned only late about the sixth school (community school), which is also quite new, we refer in the further work to the original five schools, which are the basis of our requirements analysis. For the sake of completeness, we included the sixth school in Table 1 . After analyzing the community school, we can say that the result of this review would not have changed if it had been included, on the contrary, the principles of this school harmonize well with the characteristics of the BT. However, it should get considered in future research work.

Today's communication technologies have opened up the way to practice open science; in detail, the methods for producing, storing, sharing, and accessing information have been progressing, and new research opportunities have developed ( Nentwich, 2003 ). Opening research processes provides, among other things, the chance to get valuable feedback from other researchers for work in progress, for example, through a platform like the Open Science Framework (OSF) 12 ( Bartling and Friesike, 2014 ). It can be called scientific-self correction if the scientific community and also non-experts are able to access research data while it is still in process and to provide feedback in the form of possible mistakes and potential improvements of the underlying work. Such an approach can also help to find solutions to specific problems more efficiently ( Bartling and Friesike, 2014 ).

Adjustments in science are needed because many studies in different scientific fields, for example, medicine, psychology, and computer science are irreproducible ( Schooler, 2014 ; ASCB, 2015 ; Baker and Penny, 2016 ; Smith, 2017 ); sometimes even the original researchers are not able to reproduce the results of their earlier experiments ( Pashler and Wagenmakers, 2012 ). That situation is known as reproducibility crisis, and the open principles are a promising approach to mitigate such a problem, as it can make research more transparent and understandable. We would also like to mention that there are critical voices that do not see a reproducibility crisis in science and calling it a narrative. For example, Fanelli (2018) concludes a literature review on that topic with the statement that it is empirically unsupported to say science would be undergoing a reproducibility crisis. Rather, it would be counterproductive fostering cynicism and indifference among young researchers instead of inspiring them to do more and better research.

Researchers usually aggregate and compress their collected research data for their final publication to meet the requirements of journals and especially conferences that request to stay within a specific limit of pages. In computer science, the cap for full papers on conferences is mostly ten pages ( Gray, 2009 ). So other researchers often have no access to the unedited raw data that can be very useful for the understanding and reproduction of the results of a paper. The aggregated data often lacks the needed degree of detail to reproduce the process of creation ( Murray-Rust, 2008 ). The transparency of open science shall serve as an example of how it can foster and improve general scientific procedures. However, researchers need a secure and trustable environment for that purpose.

In addition to the raw data, researchers create further content such as ideas and study designs in early research phases that usually do not get published. If the experiments and analysis give negative results, the same picture appears since the focus is on publishability ( Nosek et al., 2012 ) and publication bias for positive results exist ( Matosin et al., 2014 ; Van Assen et al., 2014 ; Mlinarić et al., 2017 ). So, the current system in science leads to the waste of much potentially valuable data ( Van Assen et al., 2014 ; Mlinarić et al., 2017 ). An open research culture during all phases along the research cycle with published supporting data can enhance the quality of work. Supplementary, from an economic perspective, researchers may check ongoing projects to prevent the waste of time and resources for topics that are already getting processed by others.

Open science still has to overcome significant obstacles in different dimensions to get widely applied. Most of the points mentioned here require such drastic changes in research processes and habits and behaviors of researchers that their realization in the foreseeable future is doubtful. For example, the traditional workflows of researchers need to be changed; they usually do not contain steps to publish research data or publicly discuss different topics about it before the final publication. Research is most of the time taking place in a closed institutional framework without the integration of individuals from the outside, so these barriers need to put down to build an open research environment. Around the whole open science discussion, a legislative framework has to be developed, but not only on the national level; it has to be international to set the global rules for the disclosure of incoming and outgoing data and also to protect the rights of all people involved. It is also a discussion of how the crediting of contributions is working fairly when researchers are creating micro-contributions (data sets, hypothesis, ideas, and reviews) ( Tennant, 2018 ) in addition to traditional publications.

Altogether, in this section, we described on the one side different challenges and problems of science and the other side how open science can mitigate them and what benefits it can deliver if a suitable technical infrastructure is found. For that purpose, we are analyzing in the next section what specific requirements such an open science infrastructure has to fulfill.

3.2. Requirement Analysis for an Infrastructure

With the underlying five schools of thought by Fecher and Friesike (2014) , we systematically analyzed what requirements for an open science infrastructure following the open principles are. Therefore, we first made a detailed requirement list of every school and compressed them to a superordinate and more abstract level. Then we identified cross-school elements of such an ecosystem by checking if certain schools sharing the same needs. Finally, we have assigned all other requirements to the specific schools. Out of this analysis, we created a overview of requirements (see Figure 1 ). In the following paragraphs, we briefly describe all single points.

Figure 1 . Overview of general and specific requirements for an open science infrastructure/ecosystem.

One essential requirement of an open science infrastructure is to provide a collaborative environment , which means that researchers and also non-experts are able to work together, author collaboratively, and share information, materials, reagents on different projects ( Hunter and Leahey, 2008 ; Tacke, 2010 ). The performance in a (research) team compared to single researchers is far more effective and efficient on different levels, for example, better quality, higher productivity, and fewer errors by additional review bodies. The requirements Open Data and Open Access are supporting the collaborative environment while they address different scientific problems. Open Access portrays free access to knowledge, for example, scientific publications ( Cribb and Sari, 2010 ; Rufai et al., 2011 ; Sitek and Bertelmann, 2014 ). Quite often, research publications are behind a paywall with continuously increasing costs ( Carroll, 2011 ) that can hinder researchers and the general public from reading and citing them; ironically, research is often funded by tax money. Among other researchers, Cribb and Sari describe the access to knowledge as a necessity for human development ( Cribb and Sari, 2010 ; Phelps et al., 2012 ). One aspect of Open Data addresses the reuse of published scientific data ( Pampel and Dallmeier-Tiessen, 2014 ). Often, an academic third party like a publisher holds the rights, so the scientific community is not allowed to reuse this data without permission ( Murray-Rust, 2008 ; Molloy, 2011 ). Considering the philosophy behind open science, research results should be reusable preventing the waste of resources for collecting already existing data again and allowing for synergies between researchers and their works ( Murray-Rust, 2008 ).

Everyone should be able to express their opinion freely without being censored in any way as long as the law is respected. The same applies to science ( Salyers, 2002 ) and related networks; censorship should not be possible in any way by any participant. We think that there should not be an entity that controls a scientific infrastructure and data on it; rather, collaborative management is preferable in an open science environment. However, each platform needs a governance model that provides the framework for the user community. In this regard, still many questions have to be answered in future work, for example, who initiates, develops, and maintains the platform, who creates the rules and decides about contributions and which parties are trustworthy?

Another essential requirement is to provide an identification and reputation system that can identify researchers and other participants of the ecosystem and link them to their contributions. So, it should be possible to credit the valuable work and invested effort of all contributors appropriately and to calculate scientific metrics, for example, impact factor or h-index to build a reputation ( Woolston, 2015 ). The last general requirement we identified is that every element in a technical infrastructure should be extensible to make sure the whole ecosystem is sustainable ( De Roure et al., 2008 ). Extensibility is vital, especially in today's digital age in which computer technology develops so fast and delivers more efficient new tools regularly. Overall, it allows the community of the ecosystem to upgrade and improve the single components steadily, so no costly and time-consuming substitutes are necessary for the long-term.

The five schools of thought have their own more specific requirements for an open science ecosystem. The democratic school demands incentives for collaboration and sharing of data that are crucial for such an environment ( Arazy et al., 2006 ; De Roure et al., 2008 ; Haeussler, 2011 ). Participants should get an extrinsic motivation, for example, a form of counter-value ( Haeussler, 2011 ) for sharing their data and contributions in an open infrastructure ( De Roure et al., 2008 ). Incentives can also work in harmony with a reputation system. The democratic school also highlights that all users in an open science environment should be treated equally , for example, in the perspective of access to knowledge ( Rufai et al., 2011 ; Fecher and Friesike, 2014 ). So, no participant has more rights than another except in terms of administration and governance of such an infrastructure, which represents a special matter. Decisions about the future development of an ecosystem and how valuable contributions are should be made democratically by independent experts, so in our case, people who have experience in research and the scientific system.

In the view of the pragmatic school , the integration of an open research process into existing established procedures needs to be as simple as possible to convince researchers to change or adjust their workflows . If it is complex, costly, or challenging, it will be a deterrent, so most researchers will not adapt their processes and hence not participate in the network. The complexity also affects the willingness of the researchers to provide and share data and content in general ( Vision, 2010 ). If integration takes too much time, or there are no visible incentives or counter-values, information very likely will not be shared ( Campbell et al., 2002 ; Vision, 2010 ; Boulton et al., 2011 ). The effort needed is a crucial element for a working open infrastructure; simplicity lays the foundation for participation and complements the used incentive systems.

Crowdfunding opportunities in an open science ecosystem are one of the requirements of the public school . It allows that every participant can decide privately to fund individual research projects that are following promising goals; thus, crowdfunding expands funding methods of research. In exchange, these backers can get monetary or non-monetary (for example, usage rights) benefits ( Fecher and Friesike, 2014 ). Furthermore, the public school aims to record the trail of research for every research object like papers, data sets, ideas, used tools, results, and hypothesis so that the involved people get credit for these objects according to their contribution. It is also an important factor to retrace the creation process of, for example, a study or an experiment to replicate its results. A chronological chain of milestones about data creation, and also the availability of raw data can be part of the solution for the current reproducibility crisis. There are two crucial points to fulfill the requirement of a trail of research. First, the researchers need to make proper documentation about their works what they always should do ( Vasilevsky et al., 2013 ). Second, the underlying technical system should record all transactions immutable, so censoring is not possible in any way afterwards.

Another part of the public school is citizen science ( Hand, 2010 ; Gura, 2013 ) that allows regular citizens to participate in certain research projects, even if they have no specific experience in science. A fictional example would be the setting up of temperature sensors in the homes of various participating citizens throughout the world; thus, the global average temperature can be determined. There are several examples of citizen science projects ( Irwin, 2006 ; Hand, 2010 ; Catlin-Groves, 2012 ) - see Rosetta@Home 13 , EchidnaCSI 14 , or eOceans 15 . Opening up research processes to citizens can be beneficial, but it strongly depends on the nature and goals of the particular project ( Irwin, 2006 ; Powell and Colin, 2009 ; Gura, 2013 ). Therefore, an open science infrastructure should provide possibilities to integrate the wide publicity into research.

The infrastructural school contains the requirement of using open source code and tools in projects that include the development of new software ( Nentwich, 2003 ). That procedure enables other researchers to use the same algorithms and processes, which eases the reproduction of results and a general understanding of unknown programs. Schubotz et al. (2018) published a practical guide about using open source tools over the complete research cycle that supports researching by the open principles. One more requirement of the infrastructural school is the ability to share resources like digital storage space or computing power; one example is the OSG ( Pordes et al., 2007 ; Altunay et al., 2011 ) we mentioned. We also see the potential to share workforce for different research projects if they require it.

Measurement school focuses on standards of measuring metrics of old (like print journals and conferences) and new, mainly internet-based (for example, open access journals, blogs, and social media platforms) publishing formats ( Weller and Puschmann, 2011 ; Priem et al., 2012 ; Yeong and Abdullah, 2012 ). So, for an open science infrastructure, the school demands the capability to calculate old and potentially new metrics to create a measurable environment for the participants. Performance values are substantial for a reputation system and are an excellent possibility to provide incentives in the form of key figures that researchers can improve by their work. The measurement school contains a second requirement that is essential for an open infrastructure; there must be interfaces to connect internal and external systems . In that way, participants have the opportunity to share all kind of data from their own software with the ecosystem and to add new external tools and functions.

4. Blockchain Technology

In this section, we briefly describe the blockchain technology (BT), its characteristics, and functionalities to provide fundamental knowledge about it (section 4.1). After that, we compare the requirements of an open science infrastructure (section 3.2) with the characteristics of the BT (section 4.2). Finally, we present an overview matrix and several examples showing that the technology as a technical basis fulfills the requirements and hence suits as a solution.

4.1. Overview

When talking about BT, the distributed ledger technology needs to get mentioned since it is an umbrella term that includes blockchains as one type ( Benčić and Podnar Žarko, 2018 ). A distributed ledger uses independent systems (nodes) to record, share, and synchronize transactions in a decentralized network ( Kakavand et al., 2017 ). A blockchain works similar but organizes its data into blocks which are cryptographically and chronologically linked together and also may use other kinds of consensus mechanisms and smart contracts ( Anwar, 2019 ). Haber and Stornetta did already basic work for the BT in 1991 by describing a cryptographically secured chain ( Haber and Stornetta, 1991 ), and in 1993 they and colleagues improved that idea with certain functionalities like timestamping ( Bayer et al., 1993 ). Their design still had some flaws, for example, the double-spending problem ( Chohan, 2018 ) and the need for a trusted party for validating all transactions.

In 2008 a pseudonym “Satoshi Nakamoto” released a whitepaper about a novel peer-to-peer-based digital currency called “Bitcoin” ( Nakamoto, 2008 ) that overcame these flaws. Finally, the Bitcoin network went live in 2009 and had a wild journey in the context of its market value (short time over 20,000$ 16 ) and media relevance. It gained most popularity through the high number of news about its value development. We refer to a Wikipedia article 17 that contains numerous sources to reconstruct the detailed history of Bitcoin. Since 2009 many more cryptocurrencies have been developed (so far over 2,000 different currencies) and BT got noticed as a technology that not only can provide an infrastructural environment to manage currencies but also it is enabling the realization of much more use cases ( Casino et al., 2018 ). Due to the possibilities, a research offensive started a few years ago by researchers from all over the world to analyze the use of BT in many different areas ( Casino et al., 2018 ).

The BT does nothing new in a perspective of its single elements, but as a bulk, these elements (for example, decentralization, immutability, transparency, and cryptographic hashing) are unique and avoiding the double-spending problem ( Nakamoto, 2008 ; Beck et al., 2016 ). A blockchain network works without a centralized server. Transactions made in such a network are verified by the decentralized nodes (user systems) ( Abraham and Mahlkhi, 2017 ; Zheng et al., 2017 ) and stored in so-called blocks with a timestamp ( Gipp et al., 2015 ; Lin and Liao, 2017 ). The size limit of blocks can differ between varying blockchains. The blocks are getting linked in chronological order because every one of them (except the first “genesis” block) contains the cryptographic hash of the previous one, so they form a chain ( Beck et al., 2016 ; Crosby et al., 2016 ). The block hash considers not only structural data of a specific block but also its content like, for example, transactions.

It depends on the blockchain whether users can store complete files on-chain or they need to use off-chain solutions like a cloud or an InterPlanetary File System (IPFS) ( Benet, 2014 ) due to file sizes. An IPFS is a peer-to-peer distributed file system for storing and sharing data. It connects computing devices with the same network of data, and each device holds and distributes a portion of the overall data. In relation with a blockchain, the chain only stores an associated hash that references to the actual file on an IPFS. Note, that off-chain solutions (sometimes referred to as “second-layer” blockchain solutions) introduce new challenges and are an interesting research topic on their own, but one that goes beyond the scope of this paper.

In general, a blockchain is a type of database that only supports reading and appending ( Swan, 2015a ; Yli-Huumo et al., 2016 ). Due to its decentralized architecture, it operates as a peer-to-peer network, so users (peers) are interacting directly with each other without the need of trusted intermediaries or authorities ( Hoffmann, 2015 ; Catalini and Gans, 2016 ; Christidis and Devetsikiotis, 2016 ) calls it “trustless trust.” Participants that trade with each other make an agreement for transferring, for example, physical or digital assets ( Casino et al., 2018 ). The nodes of the other users in the network are then verifying the transaction by the programmed rules of the system to make sure everything is valid before it gets executed ( Nakamoto, 2008 ). The verification is essential because all records and transactions in a blockchain are immutable (tamperproof) ( Gipp et al., 2015 ; Zyskind et al., 2015 ). The consensus mechanism of the network is responsible for how verifications for the users are working. As an example, we mention the consensus mechanism Proof-of-Work (PoW) ( Nakamoto, 2008 ; Tschorsch and Scheuermann, 2016 ) which is, among other blockchains, used in the Bitcoin network and is the best-known method, but heavily criticized for its high energy consumption ( O'Dwyer and Malone, 2014 ). Another one is Proof-of-Stake (PoS) ( King and Nadal, 2012 ; BitFury Group, 2015 ; Tschorsch and Scheuermann, 2016 ; Zheng et al., 2017 ) that offers a more efficient way for verification and consensus finding, in terms of energy consumption and performance.

Literature categorizes blockchain networks in terms of their access and governance system into the following different types: public, private, and consortium, which is also called federated ( Buterin, 2015 ; Swanson, 2015 ; Kravchenko, 2016 ; Zheng et al., 2017 ). Additionally, they become separated in perspective of their consensus process into permissionless and permissioned infrastructures; these are getting combined with the various blockchain types. In public (permissionless) blockchains like Bitcoin, everyone can join and participate in the system. In private and consortium (permissioned) blockchains, only users have access who are on a whitelist; typically, parties that know each other. Other combinations of the types and consensus process permissions are also possible. For more information and a comparison between the different kind of blockchains, we refer to Zheng et al. (2017) and Casino et al. (2018) .

Application programming interfaces (APIs) are essential for a blockchain to connect off-chain (external) hardware and software with the network. It enables communication as well as the transmission and exchange of data between the systems ( Linn and Koo, 2016 ; Liang et al., 2017 ). In such a way, external applications (including web-services, Beck et al., 2016 ) can integrate the characteristics and functionalities of an existing blockchain for specific use cases ( Linn and Koo, 2016 ; Xu et al., 2016 ). For example, it is possible to hash and store research data directly from external sensors, algorithms, and other data creating processes. So, an API is an important feature of a blockchain in terms of interoperability that developers always should provide and document to maximize the blockchain's potential and ease its use.

BT has developed continuously; Swan (2015a) describes three evolutions (Blockchain 1.0, 2.0, and 3.0) that led to new possibilities of using the technology to realize steadily more complex applications and projects. Ethereum ( Buterin, 2014 ) is a blockchain application that provides an infrastructure, comparable to an operating system, which everyone can build their applications on top without the need of the cost-intensive development of an own blockchain. Ethereum introduced smart contracts (SCs) that are programmable in specific languages, for example, Java, GO, and Solidity ( Dannen, 2017 ), and allowing for the automatic enforcement of a digital contract with typically if-then clauses ( Bhargavan et al., 2016 ; Christidis and Devetsikiotis, 2016 ; Kosba et al., 2016 ). There are even projects to create complete decentralized autonomous organizations (DAOs) to automate organizational governance and decision-making with SCs ( Swan, 2015b ; Jentzsch, 2016 ).

We noticed that there are slightly different characterizations of BT in the literature ( Aste et al., 2017 ; Puthal et al., 2018 ; Treiblmaier, 2019 ; Viriyasitavat and Hoonsopon, 2019 ). Therefore, we summarized the properties of the technology and made the following compressed list of relevant characteristics concerning the open science use case.

• Decentralization : A blockchain is a distributed redundant peer-to-peer system of nodes each storing the whole blockchain or a part of it ( Abraham and Mahlkhi, 2017 ; Zheng et al., 2017 ). The architecture even allows for distributing software and other content through the network automatically ( Kiyomoto et al., 2017 ). Further, decentralization also eliminates a potential single point of failure and removes the dependency of a central authority that has to be trusted ( Kshetri, 2018 ).

• Cryptographic Hashing : Due to the hashed connection embedded in every block of a blockchain to the previous block, a chronological chain gets created ( Nakamoto, 2008 ; Gervais et al., 2016 ). Besides the consensus mechanism, hashing ensures that the complete chain, inclusive the content, cannot be altered because a change would affect one specific hash value, and from there one, all subsequent hash values, and hence the chain would get invalid ( Zheng et al., 2017 ). It also allows generating a unique hash of files of any size to create an identifier. For more information about the hashing process, see the following references ( Zain and Clarke, 2007 ; Nakamoto, 2008 ; Lemieux, 2016 ).

• Timestamping : Every record (block creation, transaction, data storage) in a blockchain gets chronologically timestamped. It provides traceability, transparency, and full transaction history for the users ( Nakamoto, 2008 ; Gipp et al., 2015 ; Mattila, 2016 ; Zheng et al., 2018 ). Timestamps in combination with a cryptographic hash can also be used, for example, as a Proof-of-Existence for certain information at a particular time ( Gipp et al., 2015 ).

• Immutability (Append-Only) : Data, once stored on the blockchain, cannot be altered or deleted anymore; the cryptographic hashing and decentralized validation (consensus) process ensure that ( Swan, 2015a ; Yli-Huumo et al., 2016 ). Exceptions are specific attacks like the 51%-attack, see Dowd and Hutchinson (2015) for more information.

• Consensus Mechanism : They define how users validate transactions in a blockchain among each other ( Abraham and Mahlkhi, 2017 ; Zheng et al., 2017 ). Since the Bitcoin blockchain and PoW, many new unique methods and combinations of existing consensus procedures got developed and implemented in new blockchains. For more information about consensus mechanisms, see Zheng et al. (2017) , Abraham and Mahlkhi (2017) , and Nguyen and Kim (2018) .

• Access and Governance System : Every blockchain gets also characterized through its access (public/consortium/private) ( Peters and Panayi, 2016 ; Lin and Liao, 2017 ) and governance system (permissionless/permissioned) ( Gervais et al., 2016 ; Peters and Panayi, 2016 ). These properties are crucial to the potential use cases ( Lin and Liao, 2017 ).

Note, that the characteristics mentioned above are not exclusive to BT. As mentioned in the introduction, there exist other approaches that also have one or more of these properties.

4.2. Blockchain Technology as an Open Science Infrastructure

In this section, we compare the characteristics of BT with the needs of an open science infrastructure. With this, we study whether the technology suits as a foundation. Therefore, we made a matrix that shows which characteristics are important for the specific requirements and can meet them (see Figure 2 ). It is crucial to understand the matrix as a whole because several demands and characteristics complement each other. For example, it is useful or needed for many functions like for providing a trail of research that there is no censorship possible in a blockchain network to provide a trustworthy environment ( Swan, 2015a ). Altogether, in this section, we describe, along with different examples, how the specific blockchain characteristics meet the requirements of an open science infrastructure. We do not claim to make a detailed model or concept of an ecosystem.

Figure 2 . Matrix about open science infrastructure requirements and blockchain technology characteristics that are fulfilling them.

In terms of accessibility and governance , we concluded in an early analysis phase that a consortium/private blockchain makes no sense for its application as an open science infrastructure. One fundamental essence of open science is to share knowledge globally and the science process itself plus the results out of it accessible for a broad audience or even everyone ( Bartling and Friesike, 2014 ), without differentiation according to characteristics of any kind. A public blockchain is suitable and can meet that purpose while a consortium/private blockchain would restrict the access. The comparison of a permissioned and permissionless blockchain goes far more in-depth and is connected to different factors like governance models and consensus mechanisms, so it is a research review on its own. In order to gain insight, we will describe two possibilities superficially.

In a permissioned network, the governance is not taken over by all equally, but an organization (we call it committee) must be formed. One possibility could be to democratically elect the members of the committee through a network of universities and research institutions. This committee then decides how the open science infrastructure will develop or what value specific contributions in the network have. The division of roles justifies itself on the fact that non-experts / non-scientists lack the necessary experience to make well-founded decisions in such a system, which is why a permissioned blockchain is elementary with this governance model. So, users get divided into two roles (“user” and “committee user”), which differ in the ability to participate in certain decisions but have the same permissions for all other aspects.

In a permissionless network, everyone is equal in all aspects, but it also opens ways to system abuse. Therefore, a suitable consensus mechanism is mandatory to make collaborative decisions about how the underlying blockchain system is developing and also to prevent malicious behavior in the network. PoW is not the right choice for open science, not least because of its high energy consumption. Instead, more appropriate are mechanisms like PoS, which could be adopted to open science purposes. The distribution of tokens, which are representing voting rights in this system, could be based on scientific experience and merit. How these values are determined and composed would have to be studied in detail beforehand. However, this approach would make the use of a permissionless blockchain possible, since people without a scientific background do not have to be excluded, their impact gets minimized by the size of their stake.

Both approaches have advantages and disadvantages, and it depends on many factors which method is better. There are even more ways to build such a system. A detailed examination of these approaches would be the next step toward a blockchain-based open science infrastructure but goes far beyond the goal and scope of this manuscript. In the following, we concentrate on the comparison of the identified requirements for an open science infrastructure with blockchain features.

An essential topic of an open science system is the possibility to provide a collaborative environment . BT and its decentralization can support that goal by enabling, among other things, all users to share the same data version. In detail, data consists of, for example, experiment results, communication content, drafts, open peer-reviews, and raw data. Also, as mentioned, specific groups or the whole network can make decisions collaboratively through ordinary votes that can follow, for example, a democratic approach ( Osgood, 2016 ). Subjects of these polls could be topics like the future development of the network, to add/remove specific features, or to accept/rate proposed projects and contributions. On a technical perspective, the validation and management of a blockchain infrastructure work as well collaboratively through the consensus mechanism in which all users take part. It also ensures data integrity and consistency in a blockchain.

The immutable (tamper-proof) nature of the BT is an ideal feature to fulfill the requirement to prevent censorship of any kind. As we described in section 4.1, cryptographic hashing , a consensus mechanism , and decentralization in combination guarantee the immutability of a blockchain. Participants of a network can only append data but not modify stored data. This property suits to science that should not underlie any censorship . Everyone should be able to freely express his or her opinion without getting restricted in any way. In the use case of research, it also includes the publishing of scientific work that has critical statements or topics. Overall, an open science infrastructure based on BT can provide such a censorship-free environment.

Considering data created in scientific work, we follow an approach that the data should be open for reuse with appropriate credit to the originator(s), but in reality, often a third party holds the rights for its usage ( Dulong de Rosnay, 2006 ). A blockchain-based open science network with interfaces for data import/export can serve as a solution while the contributors themselves can decide every time to publish their files for sharing and reusing ( Open Data ). In such a case cryptographic hashing plays an important role, so the originator(s) can integrate a hash value that is formed from the content itself and also the names of the authors and other meta information before the data gets published; in that way, they create a digital footprint. It prevents that someone falsely claims and obtains credit for work that other people did ( Dansinger, 2017 ). For additional security, it is always possible to check over a blockchain network the source and time of the creation of certain content ( trail of research ).

In addition to Open Data , an open science network shall represent an Open Access repository of knowledge which means in respect to the open principles that there should not be paywalls that hinder the people from acquiring knowledge for themselves and the scientific progress. A large spread of research works can also contribute to more citations and a better reputation for the authors. Paywalls are technically possible and implementable with BT, but considering the open principles and requirements we determined in section 3.2, we suggest not to integrate any to preserve a real public character. As with Open Data , of course, every participant and group must have the possibility to decide for themselves about the accessibility of their work; hashing can also be used here to create digital footprints.

To accurately reflect the reputation of researchers, an identity and reputation system is indispensable. It creates an incentive for network participants in the form of acknowledgment for their work. As a kind of database, a blockchain fits to function as an identity register to securely store pertinent user data. Each participant can upload content and contribute to the network. Therefore, a rating mechanism is mandatory to measure the quality and impact of stored data. Finally, the reputation of the participants is determinable. In detail, it shall enable all or only specific users to review and rate contributions, for example, papers and certain data like experiment results and micro-contributions to ascertain their value; Casati et al. already proposed an approach how crediting of micro-contributions may work ( Casati et al., 2011 ). Decentralization and the consensus mechanism of a blockchain network ensure that no central authority controls the data and so reputations will be created naturally and independent through the network participants and their feedback.

Similar to ResearchGate 18 and other platforms, the identities and lists of contributions must be accessible by everyone to achieve an optimal recognition of the researchers and their work. These platforms can use such a blockchain-based open science infrastructure as a shared database to access and display identities and metrics. A search engine and filters can help to guide through the users and data to find possible collaboration partners and citable work in different research phases. Linking every account to a real person allows creating a research curriculum vitae that shows the chronological research history of an individual along with all positive (prizes, awards) but also negative (proved plagiarism) milestones. An interesting optional function would be anonymous publishing that allows researchers to work on controversial or critical data and topics without the fear of negative consequences like discrediting. The user name expanded by some random characters can get hashed to prevent any traceability and create a pseudonym for publishing.

Technical infrastructures need to be sustainable. A key factor here is to provide extensible systems . The possibility to expand a blockchain is equivalent to other systems; for example, APIs are enabling to link software with an ecosystem. So, it is possible to communicate with external software and platforms to exchange all kind of content but also to use web-services and functionalities from them. Thus, the range of application scenarios can be steadily expanded. An additional reason is the speed of how technologies are developing today, which makes it crucial to provide opportunities to easily extend existing systems to avoid the need for the time and cost-intensive creation of new software. The consensus mechanism of a blockchain also plays a role since the majority of authorized users must accept a system change so that it gets implemented.

Incentives for using a network are fundamental to motivate people to join and participate. BT can provide different factors to create incentives for an open science infrastructure. One of them is security created by blockchain-based proofs (for example, Proof-of-Existence) and the trail of research that are allowing to support intellectual property protection and to determine who contributed certain content (papers, results, and supporting data) to a network. Note, that timestamping services like, for example, OriginStamp ( Gipp et al., 2015 ) do not protect intellectual property, rather only prove that some person possessed some information at a certain point in time. The protection only gets supported if research objects are timestamped immediately after creation and continuously as they change so that no one else can obtain the information beforehand. Additionally, the creation process can get traced by several timestamps.

Another incentive is decentralization that makes sure everyone has the current version of all data hence assists the dissemination of published work. People are expecting a kind of counter-value when they contribute knowledge what shall be satisfied through the access to published content of others. Another positive aspect is constructive feedback of the community for the provided material (scientific self-correction or open peer-reviews). The technology can further provide monetary incentive systems that use coins/tokens as a reward for contributions; a consensus mechanism can serve as technical implementation (more on this in sections 5.2, 5.3). So, on a technical level, BT offers the possibility to create new forms of reputation and incentives. However, they are worthless if not getting accepted by the respective target groups. The analysis presented in McKiernan et al. (2019) shows that a big part of universities and research institution rely on and trust in well-known metrics like the Journal Impact Factor (JIF) and use them in reviews, promotions, and tenure documents. It is improbable that they will supplant well-established metrics by novel BT-based approaches in the near future.

A network can offer equality of participation and governance model decoupled from a central authority, which is aligned with the open principles. That, in turn, may result in a rise of an incentive to use an open science ecosystem. Basically, in such an infrastructure, all people shall have access to science and experience the same chances to gain knowledge and improve themselves. Decentralization and an appropriate consensus mechanism can technically make sure that the users do not get differentiated by country, race, wealth, level of education, or any other characteristics. If needed, the BT is also able to manage different user roles, for example, to form a committee that collaboratively decides how a blockchain develops as we mentioned in this section.

Besides the incentives that should motivate people to use a network, it also must be simple to integrate its capabilities and services into existing workflows and external software without serious effort or costs. If that is not the case, potential users will likely refuse the system upfront. We think it should be mainly a one-time effort. Proper documentation, a sophisticated network design, and an individual easy-to-use API are essential to ease the integration of subsystems. Also, the consensus model is a relevant factor since it partially defines how much resources of storage space and computing power are needed to participate in the network. In the end, the users shall still use their familiar software to manage their projects and data but with the possibility to benefit from the provided features of a blockchain-based open science infrastructure.

In terms of sharing data and content , a blockchain guarantees that there is no single point of failure due to its decentralized characteristic. So, there is no potential data loss, and the network ensures availability as long as the connection to it exists. For storing new data in a blockchain, a consensus mechanism should validate all incoming files to avoid, for example, dangerous software like viruses or redundant data; a blockchain itself gets already redundantly stored across all users. In the perspective of content management, all originators should have the opportunity to restrict access to their content for whatever reason. Then data gets stored encrypted in a blockchain, so it is not accessible until its owner makes it open to other users; off-chain storages like a traditional database or an IPFS are connectable and usable via APIs as well. In that case, a blockchain only stores the associated hashes of the contents. We also see potential in sharing specific software licenses via an open science network, for example, to optimally use multi-user licenses.

A growing economy is crowdfunding that gained much popularity through platforms like Kickstarter 19 and GoFundMe 20 . Such a crowd-driven method also contains the potential for science to raise money or resources to realize promising research projects ( Swan, 2015a ; De Filippi, 2016 ). BT can offer a consensus controlled monetary coin/token system to allow users supporting projects of their choice. Another option is the connection of external payment systems like PayPal to enable people to invest through traditional digital ways. Concerning identities, hashed pseudonyms offer the possibility for anonymous participations. As an extension, SCs can serve to manage crowdfunding projects, for example, to distribute funds in complex subprojects, to perform votes, or to execute automatic orders and other digital actions.

Another promising element that BT can provide in an open science infrastructure is the ability to create a trail of research that chronologically shows how research objects develop. Timestamping all contributions from scratch (idea, study design) up to the finished paper allows to transparently store all transactions with related hashes in a blockchain and hence to reconstruct the research process in order to improve the reproducibility ( Benchoufi and Ravaud, 2017 ) in science and the acknowledgment of researchers. Contributors can get steadily and immutably linked to their data no matter if it is an idea, a new draft, or a finished paper. The tamper-proof property of the BT ensures that the trail cannot be changed subsequently. If uploaded data has to be changed, for example, because of mistakes or updated content, it is possible to add new versions while the old files can get marked or archived; realizable over the front-end (software or website surface) or potentially the consensus model .

Non-experts can also participate and provide valuable data in research (called citizen science ), especially in larger data collections that are consisting of simple information. In a blockchain-based open science infrastructure, participants can use digital sensors for measuring all kinds of properties and benefit from the unique characteristics of the environment. The measurements are automatically getting stored in a blockchain, so tampering or censoring is not possible ( Wortner et al., 2019 ). Sensors can produce storage-intensive data, in that case, a blockchain allows storing hashed data sets as identifiers that save a lot of space, and the associated measurements can get stored in a traditional database or an IPFS instead. Further, timestamps can complement and additionally validate time-related values like temperatures. Finally, the decentralization ensures that there is no central authority or system that users need to trust; data is always available (no single point of failure). The reuse of acquired results enables other researchers to make additional insights and to give feedback. So, they do not need to make another time-consuming/costly experiment to gather already existing information.

As an important requirement for an open science infrastructure, the source code and tools should be open and hence transparent for all users, so they can precisely understand what the algorithms and tools are doing. Openness provides trust, but also the advantage that all participants of a network can collaborate in its development and make or suggest ideas, plugins, and updates to steadily enhance the underlying ecosystem. That also involves prototypical software from researchers for their projects, so experienced programmers can help with feedback to achieve the best possible solutions. If users do not want to make their code or tools accessible, they must additionally have the possibility to encrypt them. The combination with a blockchain allows using its decentralization and the trail of research to support the management and traceability of open source projects.

Besides citizen science and individual contributions in a blockchain-based open science network, people can also participate in research by sharing their unused resources like storage space or computing time of their systems (for example, computers/servers) for scientific purposes. The decentralized peer-to-peer architecture of a blockchain provides an optimal ground to efficiently allocate resources to share them ( Vishnumurthy et al., 2003 ); a consensus mechanism can support the fair distribution. Developers may disseminate their algorithms in a corresponding network, so a multitude of systems (nodes) with different configurations tests them. Such a procedure suits to verify the stability of certain software and to prove that an algorithm delivers precise results. So, researchers are potentially able to run experiments that they could not do on their own, for example, because of a local lack of resources.

Metrics are an inherent part of science and can express, for example, the impact factor of researchers or publications and also show the rankings of conferences and journals ( Van Noorden, 2010 ). They can further serve as a factor for funding bodies to decide to whom they give their resources like in application procedures for specific research topics. We see a blockchain as a great possibility to calculate accurate and reliable metrics for all scientific stakeholders by providing and sharing of a trustable open infrastructure. BT can achieve that through decentralization and the consensus mechanism , so every node in a network participates in the calculation and verification of the key figures. Essential for the qualitative determination of metrics is the complete data foundation. As an example, a personalized impact factor shall cover the full range of a scientist's contributions. However, BT can only help to calculate and validate metrics but does not answer the question of which figures are relevant and meaningful for an open science environment. The current research metrics are a very topical and much-discussed topic ( Brembs, 2018 ; DORA, 2019 ).

The last requirement is about using connected systems that are not only beneficial for metrics. They are also useful to ease the exchange of all kind of data like experiment results, study designs, and papers. With particular APIs, it is even possible to automate the file distribution across system boundaries. For instance, if researchers store a file in their local storage, its dissemination could automatically take place in a connected infrastructure if desired. It behaves similarly with communication; users can send messages from one to another network. Such functionalities are supporting the integration of a blockchain-based infrastructure into external workflows and reducing the effort to work in two or more systems.

At the end of this section, we would also like to point out that the realization of a scientific platform is often made difficult or impossible by the lack of consistent funding. These are long-term projects that require detailed and well-considered preliminary planning and cause costs not only for development but also continuously for maintenance and expansion. Blockchain-based infrastructures also face this difficulty, but with the possibility of providing incentives such as cryptocurrencies that can create speculative value for investors. Thus, people outside the scientific environment get also addressed, but with this type of funding, called initial coin offering (ICO) ( Conley, 2017 ; Li and Mann, 2018 ), science and business inevitably merge. Two examples with scientific background are EUREKA 21 and Scienceroot 22 . The further investigation of ICOs for this purpose should be considered in the future, when the hype about BT has flattened, in order to get a realistic picture.

Altogether, in this section, we answered our first research question and described how the characteristics of the BT can fulfill the requirements of an open science infrastructure and provide many advantages regarding replication of results, transparency of research processes, and also the traceability of research objects. The current technological state is already capable of the realization of such a platform. Nevertheless, a variety of general and technical questions in terms of a suitable consensus and governance system, incentive factors, law, and data storage still have to be answered in future research work; we explain some of these issues in more detail in section 6. Current literature and projects are focusing on different goals, a few of them describing specific use cases like resource sharing, publishing, and especially reproducibility. More are following visions of holistic science platforms that are offering different functionalities to support research. Therefore, we will analyze the state-of-the-art in the next section to answer our second research question and overview what literature and projects are already available or in development and what is the current state of the BT for open science.

5. State-of-the-Art

This section starts with a description of how we analyzed the current state of research and how we categorized relevant blockchain projects to clarify our approach (section 5.1). After that, we give an overview of available literature (section 5.2) and projects (section 5.3). Finally, we summarize and discuss the state-of-the-art (section 5.4).

5.1. Research Overview

To create an outline of the current research, we have read and analyzed research papers, concepts, and applications up to April 2019 that are connecting BT and open science or are relevant in other forms to this topic. Currently, there is not much pertinent literature, but the amount is growing, suggesting that this research subject is in an early phase. Since there is little literature, it would not make sense to structure it. It is different with practical blockchain projects, of which we finally examined 60 in detail: 18% in a concept, 52% in a prototype, and 30% in a deployed status. We assigned each project to one of the six categories shown in Figure 3 to provide a structured overview of the current research situation. Some of the projects can also offer functionalities that are useful in other categories than their assigned one.

Figure 3 . Overview of categories of open science-related blockchain projects. The figures in brackets show the number of projects in the respective category.

The category Reproducibility contains projects that aim to improve the replication rate in science and so the quality of research. Resource sharing focuses on functions to share unused resources, for example, storage space and computing power. The category transparent evidence mainly revolves around proof keeping like Proof-of-Existence to prove that information existed at a certain time and was in possession of a specific person or Proof-of-Submission of manuscripts to journals or conferences. Projects with the classification of intellectual property protection focus on the protection of ideas, contributions, data, and everything an individual submits to make sure to give appropriate credit to the originators. Social Research Platforms/Repositories feature a multitude of science-related functions like communication, data storage/processing, reputation, and identity mechanisms; most projects fell into this category. Customizable infrastructures allow building individual solutions on top of existing blockchains to prevent the effort and costs to develop a custom blockchain.

In total, we investigated 83 projects (see Supplementary Material ) and excluded 23 of them because they provided insufficient information, were not mature enough to improve a scientific aspect, or were inactive/canceled. Most of the remaining projects have in common that they use BT to enhance different factors and elements of research, for example, trustability, workflows, transparency, reproducibility, and collaborations. The others offer specific mechanisms that are promising for improving processes in science. In order to show the current capabilities of the BT for open science, we will describe relevant literature (section 5.2) and different concepts, prototypes, and applications (section 5.3) in the next parts of this paper.

5.2. Literature

Since it is an early research phase, there is little literature about open science in combination with BT, but still, there are exciting and promising concepts, ideas, discussions, and approaches that we want to describe and highlight.

Dhillon wrote an article ( Dhillon, 2016 ) and with others a book section ( Dhillon et al., 2017 ) about BT and open science. They start the relevant chapter in their book with the current reproducibility crisis ( Prinz et al., 2011 ; Collins and Tabak, 2014 ; Baker and Penny, 2016 ; Gilbert et al., 2016 ) and the rare publications of negative results ( Matosin et al., 2014 ; Van Assen et al., 2014 ; Mlinarić et al., 2017 ). Dhillon et al. state that the BT has the potential to mitigate the crisis. They use a clinical trial as a practical example and define a workflow making the complete research process transparent while protecting critical data of patients ( Dhillon et al., 2017 ). Also, other publications are proposing the use of BT in the medical or biological area to provide, among other aspects, transparency and trust ( Nugent et al., 2016 ; Benchoufi and Ravaud, 2017 ; Ozercan et al., 2018 ). Further to the research process, Dhillon also proposes to apply their approach to implement a kind of reputation system (with an API) as a reward for researchers and an indicator for the quality of contributions ( Dhillon et al., 2017 ).

Another use case highlighted by Dhillon et al. is blockchain-based prediction markets, where mainly experts try to predict a specific outcome like the potential of reproducibility of an experiment ( Almenberg et al., 2009 ; Dreber et al., 2015 ; Dhillon et al., 2017 ). To create an incentive to participate, users get rewarded for the right prediction, for instance, by monetary coins/tokens of the related blockchain. An article by Extance (2017) contains similar statements saying that the BT can enhance the current replication situation in science, but he additionally mentions the potential of the technology for the peer-review process to build up trust due to immutability and transparency. But also, the article reiterates the statement made by Pagliari ( Extance, 2017 ) who expresses concerns about storing possibly incorrect data in a blockchain that are then immutable. A patent about the usage of BT in open scientific research ( Ahn et al., 2018 ) complies with the open principles and focuses on the integration of the technology into research workflows to allow such a tamper-proof sharing of information to improve the trustworthiness in science.

Bartling manages an open living document about the usage of the BT for open science that contains many promising ideas, projects, and hypothesis ( Bartling, 2018 ). It is special because everyone contributes to the paper by feedback, visions, or suggestions, so a collaborative and constructive discussion can take place about its contents. The statements in the living document are consistent with those by Dhillon suggesting to use the BT for science to enhance reproducibility, collaborations, and trust, but they advance even a step further. Besides many blockchain projects, they also introduce novel ideas for funding research, incentive systems for all kind of scientific activities, and an open repository for data sharing ( Bartling, 2018 ). For example, ICOs can be used to fund research projects ( Conley, 2017 ; Li and Mann, 2018 ). Interested parties (also citizens) can take part in funding and get a consideration for it what could be a later service (like usage rights/licenses) or monetary coins/tokens of a newly generated blockchain.

Statements in the living document criticize the publication bias for positive results because negative outcomes may also be valuable and prevent the waste of time and money that researchers are using for experiments that already failed for others. In that sense, Chen et al. (2018) propose an architecture for blockchain-based provenance sharing of scientific workflows to provide a secure and easy way for scientists to share their research data, for instance, to prevent the waste of resources. Bartling also founded a company “BFS Blockchain for Science” 23 that aims to foster the usage of BT in science, among other things, by organizing conferences/workshops 24 , supporting blockchain projects/startups and upcoming developers with relevant knowledge, and providing new ideas. Dhillon's and Bartling's suggestions match Rachovitsa's statements ( Rachovitsa, 2018 ). She mentions the potential of the BT to implement novel incentive models and to improve the transparency of open data and open access systems while enabling researchers to manage their intellectual property through SCs.

van Rossum (2017 , 2018) also identifies blockchain as a technology that can foster especially open science in many aspects hence corresponding to most of the statements by Dhillon, Bartling, and Rachovitsa. In addition, he highlights that BT can change the role of academic publishers in the future. He notes an increasing commercial interest in science, dominated by a few large publishers who established paywalls around research works to make a profit out of them ( van Rossum, 2017 ). On top, focusing on current metrics can lead researchers to pursue the goal of high ranking rather than primarily doing good research. BT can help to mitigate such problems, but a significant factor that Van Rossum mentions is the adoption rate of the technology by the scientific community and its stakeholders. Acceptance will have a decisive role in the futures development of the technology for open science and other application areas. Another success factor he brings up is the existence of a common communication interface, so a trustworthy collaborative environment gets created.

The report ( van Rossum, 2017 ) of Van Rossum contains two interviews as well; one with Efke Smit 25 and another one with Philipp Sandner 26 . Smit says that we already have a working academic world and puts into question why the scientific community should take the effort and costs of changing to a new system with BT. She summarizes that the technology, whether it is widely established or not, will be probably unnoticed anyway by non-geeks; the future will show if blockchains prove themselves as a game-changer or as a hype. Sandner sees the potential for using BT and SCs in science; as application examples, he mentions funding, publishing, scholarly communication, and incentive systems. Further literature and a web article by Bell et al. (2017) , Brock (2018) , and Opoku-Agyemang (2017) likewise describe the many possibilities of BT to improve science and all kind of research activities as statistical analyses, data evaluations, and medical trials.

Intellectual property is a regular output in science which can be very valuable and should be protected so others are not able to steal it and the originator can appropriately be credited. de La Rosa et al. (2017) analyzed how blockchain-based protection of intellectual property in open innovation processes can work; such an approach is also critical for scientific environments. The safeguarding has to start right at the first appearance of an idea ( Schönhals et al., 2018 ) to provide a trustworthy system and to motivate researchers and other individuals for open collaborations. As a simple example, an idea that appears the first time can be timestamped and immutably stored in a blockchain to prove its existence at a certain time point; also, originators can add metadata like their names to these transactions.

Since most projects we found are social research platforms and repositories that allow their users to discuss ideas and hypothesis openly before they are processed, we see the protection of intellectual property as fundamental. de La Rosa et al. (2017) conclude that the BT can provide great benefits for open innovation processes and the protection of its outcomes; other researchers confirm this in their research papers ( Gürkaynak et al., 2018 ; Rivière, 2018 ). But there is still much to do: it lacks approaches to prevent unauthorized reuse of intellectual property, and most existing blockchain applications are not mature yet ( Schönhals et al., 2019 ). A few more ideas about this topic can be found here 27 , 28 .

Another core part of the scientific process is the peer-review of submitted research work. It is one of the most important activities because not only the acceptance of papers for conferences or journals and hence the progression of PhD students and researchers are depending on it, but also research grants and hiring are related to it. Therefore, reviews need to be neutral, trustworthy, and transparent without any bias to provide a fair chance for all participants in science. But there are some concerns about the fairness and quality of today's review system and the opportunities to abuse it ( Smith, 2006 ; Tennant et al., 2017 ). Most of the time, peer-review is a black-box process, so reviewers are anonymous (authors mostly not), and malicious behavior is difficult to detect. Such lack of transparency can lead to a loss of trust. In that regard, several researchers see potential in the BT to improve and open up the peer-review process ( Spearpoint, 2017 ; Tennant et al., 2017 ; Avital, 2018 ; Jan et al., 2018 ).

In a multi-disciplinary study of Tennant et al. (2017) about innovations in peer-review, they identified the BT as a potential future model with promising possibilities. Examples are incentive systems with coins or tokens that reward the reviewers for their efforts, and authentication/certification methods for fraud control and author protection. They conclude that the technology can enhance the quality and responsiveness of the review process. Both Avital (2018) and Spearpoint (2017) , are independently underpinning these statements by proposing two different blockchain-based systems that use monetary incentives along with new metrics to address inefficiencies of the review process. Jan et al. (2018) are also sharing the opinion and utilized BT and SCs to develop a peer-review prototype.

Tenorio-Fornés et al. (2019) criticize the oligopolistic position of the publishers in academia regarding policies, embargo periods, and restrictions about the dissemination of data and propose a blockchain-based publication system for open science to address that. They say that the BT has the potential to realize the promise of open access with new models of data distribution. Another interesting idea comes from Hoffmann et al. (2018) who are naming their approach Smart Papers, which are SCs that are managing attributions and annotations of scholar publications. They aim to use the trustworthy environment of the BT to provide a framework for collaborative authoring and to implement a web client in future work.

Janowicz et al. (2018) wrote a paper about blockchain-based open science and publishing. They propose an informal model of how to use the BT to enhance and partly automate the general scientific workflow, particularly academic publishing, with the support of SCs. Besides their primary focus, they identified promising use cases of the technology in open science that we partially already mentioned in this section, for example, creating transparency of the peer-review process, storing and tracing all kind of scientific data to foster reproducibility, and connecting researchers to potential investors and vice versa. Moreover, managing intellectual property, democratizing of science for significant decisions in the community, and opening up black boxes like algorithms or closed data.

But Janowicz et al. (2018) also express concerns for the implementation of BT for open science. For instance, retractions are normal processes in science due to mistakes, updated papers, plagiarism, and other reasons but in case of a blockchain data is immutable once it is stored; a reasonable handling for such a use case has to be found. Another critical concern is the question of how and to what extent financial incentives may lead to unintended behavior since quite a few projects are using monetary aspects as motivation for their users. There is a chance that the focus of researchers could shift from actual research and knowledge creation to an economic mindset what should not be a major driver in science. Finally, Janowicz et al. (2018) criticize the high number of blockchain-based concepts that barely contain precise details to understand their exact workings and value proposition. We also found several projects in our analysis that did not provide enough information to understand their intentions or applications technically so that we can confirm this statement.

5.3. Projects

In the following sections, we describe use cases of the six categories we defined along with associated projects. We do not aim to present every single project in detail as it would be far beyond the scope of this paper; moreover, several of them are similar and follow more or less the same goals. Also, we include some approaches and applications that are not focused on science but contain specific interesting functions or mechanisms that are promising if transferred to blockchain-based research workflows. Our analysis includes projects that are at concept, prototype, or deployed status; some of them are commercial. Regarding references, we preferred research papers or whitepapers. If these were not available, we referred to the related website or GitHub repository.

5.3.1. Social Research Platform/Repository

We classified most of the projects that we analyzed as social research platforms/repositories . Especially in this category, the concepts and applications often provide many overlapping functionalities and have similar goals. Potential use cases are to create open platforms, repositories, or marketplaces to support collaborations in science and to allow open access to research data hence improving the reproducibility of experiments, studies, and other kinds of research. Typically, they contain much more capabilities like communication methods, reputation and identity mechanisms, and incentive systems for their users. Further, the traceability of the BT serves as protection of the contributors and creates a trustworthy and transparent environment. Two exemplary open science platform projects are Frankl (2018) and Aletheia (2018) .

Some blockchain-based projects also aim to open up the publishing process and to provide incentive mechanisms for peer-reviewers in order to be more transparent, trustworthy, and rewarding; they function similar to an open access journal. Examples are Publish and Evaluate Online (PEvO) ( Wolf et al., 2016 ), EUREKA ( EUREKA, 2019 ), and the concept of an academic endorsement system (AES) ( Anonymous, 2016 ) that was published anonymously. The AES paper criticizes specific aspects of the scientific system. Their approach involves, among other features, the possibility for researchers to individually endorse the work of others with a currency of the network. Steemit (2019) , as a non-scientific application supports such a mechanism along with a reputation system so users can independently reward other users for their content/contributions. There are also existing projects that, in addition to features for collaboration, research management, and publishing, also provide funding methods for research, for example, Scienceroot ( Günther and Chirita, 2018 ), the Open Science Network (OSN) ( OSN, 2019 ), the Decentralized Research Platform (DEIP) ( DEIP, 2018 ), and Orvium ( Orvium, 2018 ).

In order to gain more trust and transparency in their fund granting for research, The National Research Council of Canada created a blockchain-based prototype that is named NRC-IRAD ( NRC-IRAP, 2019 ) to proactively publish grants and contribution data in real-time. We think this approach also has great potential for other countries. It works as a public blackboard for researchers and their groups or organizations who can apply for certain government-funded research topics. Making research data workflows FAIR (findable, accessible, interoperable, and reusable/reproducible) with using a decentralized data infrastructure is the goal of DaMaHub (Data Management Hub) ( DaMaHub, 2019 ). Their first implementations combine BT to transparently record and track all system transactions and IPFS for data searching and storage. In case of content dissemination, LBRY (not science-related) ( LBRY, 2019 ) has an interesting approach as a community-operated digital marketplace in which content owners can set individual fees for their contents without any dependence on intermediaries; similar to WildSpark ( Tabrizi and Konforty, 2017 ). Such a method transferred to science may allow researchers to publish, distribute, and potentially monetize their work individually. The system could also be expanded with a peer-review process to create a blockchain-based journal.

Matryx ( McCloskey et al., 2019 ) follows a novel approach and aims to incentivize the collaboration in science to foster the creation of innovative ideas and projects. Besides providing a marketplace for buying and selling digital assets, it also uses a blockchain-based tournament system in which, for example, a user can create an individual challenge with a particular bounty that gets paid off as a reward to the user who solves the problem. An exceptional topic is focused by Space Decentral (2018) that is a DAO whose aim it is to let the network's community in control for deciding how the science space programs on the platform will continue; functions as crowdfunding, sharing of research data, and peer-reviewing are integrated.

ScientificCoin (2018) is a crowdfunding platform that attempts to determine the potential/risk of scientific projects by several different factors in a mathematical algorithm and expert evaluation. Target groups are researchers that are searching for funds and investors. But it also opens up a way of receiving valuable feedback on research projects, which can help to identify and improve planning or methodical shortcomings. Another extraordinary blockchain-based network is Coegil (2019) , which connects decision-makers with the expertise of many people (participants of the network) to eventually being able to make decisions of high quality. Transferred to science, we see the possibility in such a kind of system to get valuable feedback for research works by experts; especially young PhD students can benefit by that in preparation of their first publications.

The project bloxberg ( Vengadasalam et al., 2019 ) provides a blockchain network that consists of several research organizations that form a consortium and administrating the ecosystem. They aim to foster, among other things, sharing of data, collaboration, peer-reviewing, handling of research claims, and publishing with the help of a secure global environment. The bloxberg system also allows using it as a base structure to develop new applications on it. ARTiFACTS ( Kochalko et al., 2018 ) uses this infrastructure to build a research platform that provides indexing functionalities and a dashboard that displays multiple statistics on the stored content of a researcher. So, it is capable of creating a transparent data trail for research objects and determining several scientific metrics; the developers also plan to extend their system with a blockchain-based digital identity network.

A further blockchain infrastructure that focuses especially on the validation of data integrity in biomedical studies is TrialChain ( Dai et al., 2018 ). This idea is also interesting for other scientific areas because data integrity plays a central role in all kinds of studies/experiments. One more noteworthy and ambitious approach is Project Aiur ( Project Aiur, 2018 ), which envisions building an open platform for validated knowledge without access barriers, publication bias, and information overload while all research is reproducible. To achieve their vision, they aim to combine a repository and a community-governed artificial intelligence that is capable of automating knowledge validation.

5.3.2. Reproducibility

Blockchain projects with a focus on reproducibility in science or the potential of improving the replication rate are subject in this category. Furlanello et al. (2017) proposed their PROBO-network, which is an approach to enhance scientific reproducibility with BT. In general, they want to solve the issue of rewarding time and expertise of scientists that are replicating research results by establishing a monetary-based incentive for them. To achieve that a researcher (proponent) publishes, for instance, a timestamped study with all supporting data in the PROBOS-blockchain and deposits a pre-determined amount of probos tokens to broadcast a request to the network, where clients (verifiers) can evaluate the quality of the study and verify its reproducibility; verifiers getting rewarded by the deposited tokens of the proponent ( Furlanello et al., 2017 ). Especially in the medical sector reproduction of results is vital, for example, to produce reliable drugs for living test subjects and the global market but also to build upon promising and robust basics to prevent resource wasting with irreproducible research.

Forecasting and prediction markets like Gnosis (2017) , Hivemind (2019) , and Peterson et al. (2018) are another kind of promising blockchain-based projects. These markets involve people with expertise who predict or confirm specific outcomes based on existing information, representing a concept of collective intelligence. Such systems are usable in many application fields, for instance, in science to support reproducibility. Among other things, its participants can forecast or confirm the replication probability of experiment results. That procedure is suitable to obtain information in a short time to optimally allocate limited resources into reproduction projects ( Dreber et al., 2015 ). The incentive for the users of these platforms usually is of a monetary nature because they get a pre-deposited coin/token reward for correct predictions and confirmations from the creators of requests.

The next blockchain-based project that we want to mention because of its unique approach is Dsensor (2015) even though it seems stopped or canceled. There was no actual news for over a year, and the announced whitepaper is overdue for 2 years, so we assume the project got aborted. It aimed to provide a computational consensus that uses relevant sensor data to determine whether a networks hypothesis is correct or not. So, if a result is measurable and the data access to necessary sensors exists, such a system would be capable of performing an automatic validation/reproduction of a specific outcome and at the same time recording it on a blockchain for securing data integrity.

5.3.3. Transparent Evidence

This category contains projects that intend to create immutable proofs on a blockchain to verify different aspects like the existence of particular information, submission of documents, or time of actions. These digital certifications allow, for example, to support legal procedures and to provide the required security/trust for open technical infrastructures. One project is OriginStamp ( Gipp et al., 2015 ) that offers Proofs-of-Existence in the form of timestamps on the Bitcoin blockchain. So, a person can obtain evidence for being in possession of specific information at a certain time, for instance, documents, results, ideas, and all other kinds of digital assets. Further, CryptSubmit ( Gipp et al., 2017 ) uses OriginStamp as a basis to combine the timestamp functionality with a scientific manuscript management system for journals and conferences. Thus, it creates a Proof-of-Submission that serves as evidence about submission and integrity of data to prevent fraud and theft of research ( Cantrill, 2016 ; Degen, 2016 ; Dansinger, 2017 ). CryptSubmit also supports timestamped peer-reviews to enhance trust in the whole review process and can additionally serve as a basis for open peer-reviewing.

Online discussion and sharing platforms can also use BT to record all platform activities to secure the trustworthiness of messages and data. So, the first appearance of an idea or a micro-contribution gets registered and then is traceable to its originator. VirtualPatent ( Breitinger and Gipp, 2017 ) is a project that proposes such an approach. It aims to function as a social media platform that immediately timestamps every message in the system to allow open discussions about, for example, novel ideas and drafts. PUBLISHsoft (2018) has a similar but commercialized concept and a different target group as it intends to notarize and trace journalistic news; the mechanism is transferable to research data likewise.

An approach that is focusing primarily on the peer-review process in science is Blockchain for Peer Review ( BfPR, 2019 ) that aims to make the procedure more trustable. They envision to extract peer-review data from connected journal management systems to record them in a blockchain hence allowing the reviews to be independently validated. In the following, we describe two non-science related projects with noteworthy functionalities. The first project is Codex ( Codex, 2018 ) that offers its users the possibility to register digital assets. Their platform got designed for art and collectibles (for example, wine and jewelry) where no centralized title registration exists. We see the potential to use such a decentralized register for scientific publications or datasets to prove their existence and affiliation. The second project is Sovrin ( Sovrin Foundation, 2018 ), which is a blockchain-based identity management network. It provides, transferred to research, the technical opportunity to transparently link every contribution to the identities of its originators and therefore to create a scientific curriculum vitae.

5.3.4. Intellectual Property Protection

Since intellectual property is a typical output in research, it is important to protect it and the originators adequately, in special when knowledge gets patented and monetized. The projects in this category are focusing on notarization, licensing, and certifications of digital assets. These systems are usable in many application fields, but one of the most substantial is science. An already deployed and commercialized application is Bernstein ( Barulli et al., 2017 ) that aims to be a notarization service powered by BT. Its underlying system can issue ownership certifications of digital assets that get stored in a hashed form on the Bitcoin blockchain; examples are licenses, research papers, and non-disclosure agreements (NDAs). Another blockchain-based project that is additionally providing the ability to create marketplaces to monetize an idea, patent, or different kinds of intellectual property is po.et ( po.et, 2017 ). The Molecule Protocol ( Molecule, 2019 ) is combining open science and BT to build a collaborative market-based platform for discovery and funding of pharmaceutical intellectual property. They intend to connect scientists, patients, and industry to advance drug development in its transparent, secure environment.

A concept named Coalition of Automated Legal Applications Intellectual Property (COALA IP) ( De Filippi et al., 2016 ) aims to be a free community-driven protocol for establishing an open global standard in intellectual property licensing to form a consistent framework and to eliminate the dependence on central organizations. Also interesting for researchers and their contributions is Vaultitude ( Vaultitude, 2018 ) which is a large-scale project whose team is cooperating with international authorities and law firms to establish a blockchain supported Proof of Authorship for the digital assets of their users. The projects Bookchain ( Scenarex, 2019 ), Attribution Ledger ( Prescient, 2019 ), and ChainPrint ( ChainPrint, 2017 ) are concentrating on protecting and publishing intellectual property, mainly documents, books, and creative works. So, their target groups are authors, publishers, and partially printing houses, but also researchers may use such services if they want to disseminate papers, studies, or other writings. In all three cases, the uploaded data gets recorded via blockchain to create an immutable trail of information to provide trust and security before and after the publication process.

5.3.5. Resource Sharing

Resources are limited; researchers are peculiarly aware of that when some experiments are not feasible due to a local lack of materials, workforce, equipment, or funds. In this regard, a blockchain can serve as a distributor to share digital resources like storage space. Specific projects for sharing storage space, for example, to save all kind of research data securely in a blockchain environment, are Storj (Tardigrade) ( Storj Labs, 2018 ), Filecoin ( Protocol Labs, 2017 ), Sia ( Vorick and Champine, 2014 ), SAFE network ( MaidSafe, 2019 ), and Swarm ( Swarm, 2019 ) in which all individuals can participate by providing unused capacities of their computer systems. Despite that network users are storing the information of data owners, they cannot access/read them, only the owners can do that; the projects use different methods for this, among other things, encryption and file splitting. Information in the form of data is also a valuable resource that is digitally shareable. The Ocean Protocol ( Ocean Protocol, 2019 ) pursues such an approach and helps marketplaces to buy and sell mainly artificial intelligence data/services while incentivizing data reusing and sharing with a blockchain-based incentive system. This data can get used as learning material for artificial intelligences, but also can support researchers in their projects.

Besides sharing storage space and data, there are also approaches to share computing power in a blockchain network. We think a method of that kind is promising to enable, for instance, researchers to execute specific demanding computing tasks such as complex simulations. A project that aims to provide exactly this functionality hence to operate like a distributed “supercomputer” is Golem ( Golem, 2016 ). Their approach works with various nodes (providers) which are offering their unused computing power as a resource in exchange for monetary tokens. In general, other network participants (requestors) can use that provided performance to calculate, for example, algorithms, photogrammetry reconstructions, renderings of movies/CGI, and machine learning applications in an associated sandbox environment. The Golem network supports the distribution and monetization of software as well.

5.3.6. Customizable Infrastructure

Customizable infrastructures are serving as a fundament on which developers can build their designed blockchain-based networks. In contrast to custom-built blockchains, the source code gets already provided, and less know-how is needed for their realization. So, this approach saves time and funds, but it is limited in its possibilities because the underlying systems usually prescribe certain aspects like the consensus model and the basic structure of the network. Most of the projects in this category are focusing on private permissioned blockchains that have mainly companies as their target group, but still, universities and research groups can benefit from these infrastructures. Exemplary science and academic-related use cases are data tracking and auditing, education/training of students, project management, distribution of digital assets, timestamping, and the issuance of certifications. Further, it is possible to use customizable infrastructures to partly build similar applications like the projects we mentioned in the sections 5.3.1–5.3.5 but with the advantage that they can get adapted to specific demands. Also, completely new solutions are realizable.

In every case, the requirements of a project need to get evaluated to decide whether the possibilities of a provided customizable infrastructure are sufficient to fulfill them or a custom blockchain application is necessary. If the estimated quality is satisfying, there is no necessity to incur the additional effort for a new development. We found several projects that aim to provide such an infrastructural framework to build blockchains or blockchain-based applications, for example, Hyperledger ( Androulaki et al., 2018 ) from IBM, Openchain ( Openchain, 2015 ), Multichain ( Greenspan, 2015 ), Blockstack ( Ali et al., 2019 ), and DCore ( DECENT, 2019 ). In summary, we see customizable infrastructures as a perfect introduction to the BT to test its potential and suitability for diverse application scenarios and to gather the first experience in their development.

5.4. Summary and Discussion

Our review shall serve as a snapshot of the current research situation of the BT for open science with an additional view outside the box to other applications that offer useful functionalities for that scope. During the last 7 months in that we collected and analyzed practical projects, we noticed that the market is unstable. A few of them disappeared, got canceled with official statements of their developers, or are subjectively dead based on long-time inactivity. In total, more new approaches were announced in these months, so the trend we identified shows a steadily increasing number of active blockchain projects for open science. That development is also retroactively observable over the past few years.

For section 5, we diligently analyzed 35 relevant research publications (gray literature excluded) and overall 60 blockchain-based projects (see Supplementary Material ) with different application areas and classified them into six categories to structure them corresponding to their orientation. Considering the acquired knowledge, we agree that the BT has a great potential to foster open science in various aspects. Examples are a new level of trust into systems and their transparency, traceability of digital assets, higher reproducibility, innovative citizen science projects, creative incentive methods, and a generally improved research quality. Especially the realizable openness of blockchain applications and the tamper-proof recording of all transactions in a system make this technology to a suitable trustless infrastructure for open science.

In the end, a blockchain alone represents a database with a unique bulk of characteristics but without a specific sense. An integrated application like Bitcoin or Ethereum gives a purpose and functionality to it. So, we differentiate between the blockchain and application layer (includes the front-end), which need to correspond with each other to use the technology as an advantage. Therefore, in open science projects, both layers should get designed in harmony following the open principles to provide a cornerstone for a transparent and trustable environment; the prevention of non-transparency and possibilities for malicious behavior is fundamental.

If a researcher integrates BT continuously within the whole research cycle, it can be useful in every phase, also partially for experimenting if it comes to tests of algorithms or evaluation of sensorial data. As shown, there are many varieties of using the technology in science to achieve a win-win situation for all stakeholders. In combination with sophisticated application design and development, it is also able to enable new usage models regarding research management, peer-reviewing, funding, and publishing. However, the expectations must be realistic; BT is not a cure for all existing problems in science or an all-in-one solution.

During our analysis, some questions and concerns arose in terms of various projects and other aspects that should get examined in future works. Below, we will briefly describe these uncertainties; more details to the most relevant topics will follow in section 6 to answer our third research question. Many projects are introducing own incentive methods that are often of monetary nature; examples are bounty systems or coin/token rewards for specific actions. On one side, we question if it is a suitable approach to integrate such financial aspects in the research process. Would that shift the intention to create knowledge and progress in science to an economic focus? On the other side, we agree to establish new incentives for the invested time and expertise of scientists who are reproducing and confirming results/studies and peer-reviewing submitted research work for conferences and journals. Further concerns are about how to deal with bugs in already deployed hence immutable SCs, and how different nations are assessing proofs issued from a blockchain in their juristic processes.

The literature and projects also showed that a standard is missing that sets a framework for how blockchains can communicate with external software through APIs, and how data is exchanged to ease the development and integration of the BT into existing workflows. The current situation makes it difficult to identify serious blockchain-based applications. The enthusiasm around this technology led to many new project announcements in the last few years, but in the area of open science, most are in concept or prototype status as our analysis showed hence are not suitable for full integration. To prevent the waste of resources, we advise making sure only to actively use blockchain applications that are at a mature state and already providing the desired functionalities. Due to the unstable market, projects can disappear from 1 day to another, specifically because most of the time, startups are developing them that usually do not have a financial buffer.

A couple of the analyzed projects aim to make intermediaries in science obsolete. These would primarily be publishers. However, the publishers can also use the BT for their good. It provides the potential for them to partially automate distribution and peer-review processes via SCs, and to decrease their costs to manage the steadily increasing amount of knowledge and number of publications. As a synergy effect, these aspects can also be positive for researchers, for instance, through fewer publication fees and faster feedbacks. Further, publishers can open up their operations to transparently show how peer-reviewing and other activities function in order to improve their trustworthiness.

Funding bodies as one stakeholder group in science are using, among various factors, metrics for their decisions on how to distribute their financial resources to researchers and their projects. The problem is that indicators of the same researchers and publications are often differing from one research platform to another due to the circumstance that they use different databases to calculate their key figures. We think the basic technical structure of a blockchain is an excellent opportunity to create a shared, transparent storage. So, it can provide the same data for every science platform to calculate precise metrics like the impact factor of a researcher or a publication.

We also think, as mentioned in some literature, that the adoption rate of the BT will decide about its future development both in science and in all other application fields. So, the number of users is a key factor; a network without participants does not make sense. Most of the projects we analyzed had, from a subjective point of view, a non-existent or small community, so we opine that the technology needs a push explicitly for its usage in open science; maybe a big publisher, stakeholder, or a norm? Overall, it is still a fairly new technology, so it is not yet possible to say for sure how the masses will interact with it and what behavior will emerge.

In this section, we answered our second research question and gave a picture about the current research state of BT for open science along with its possibilities and uncertainties that we identified during our review.

6. Challenges and Research Potentials

In this section, we describe in the context of our third research question challenges and research potentials that we identified during our analysis. Future works should address them in order to eliminate technological and legal insecurities and to enhance the usability of the BT for open science and beyond. We focused on some of the most relevant and promising topics in our view, which got not or insufficiently investigated yet. They shall provide an impulse in the form of starting points for further research; as a positive side effect, addressing these issues can partially also foster other non-scientific areas.

We want to point out that the challenges presented in this section are very complex and profound, so we do not expect them to get resolved in the near future. For example, the correctness problem of software which is fundamental to smart contracts (see section 6.1) is around since the early days of programming, and till today a solution is not yet in sight. Therefore, the following topics are an outlook into vital pillars that need to be considered in the course of a broad integration of BT.

6.1. Risks and Validation of Smart Contracts

Trustworthiness is a key element of BT and one of its main drivers, so developers should design all aspects in their applications in a way to support and provide that property. In this regard, we see SCs that get used in many projects as critical because they can offer various possibilities for malicious behavior and are prone to crucial coding errors in their development. The ability to use Turing-complete programming languages opens up not only numerous use cases and functionalities but also increases the complexity and thus the potential for human mistakes and the number of backdoors/exploits. These can cause, for example, crashes of the processes or vulnerabilities of the program itself that may allow hackers to steal the resources that a digital contract manages ( Bigi et al., 2015 ; Atzei et al., 2017 ). The novelty of SCs justifies the circumstance that the common knowledge about their design, implementation, programming, and validation is not well developed yet.

One approach to counteract vulnerabilities of SCs is to limit the expressiveness of the underlying programming language ( Dannen, 2017 ). Another possibility is the several commercial providers of audit services that have got founded in the last years. They are checking SCs to make sure they fulfill their purpose without eventual weak points. Examples are Runtime Verification 29 and Securify 30 . In that sense, we see research potential in investigating ways to automate the formal verification of SCs through software to quickly eliminate the possibility of specific attacks ( Bigi et al., 2015 ; Luu et al., 2016 ). A further approach can be a modular construction kit to be able to build digital contracts piece by piece for reliable, simple applications. Hence no great coding skills are required, and the creation process gets eased, similar to OpenZeppelin 31 . Also, standards can generally improve the design procedure and security. There is still much to do on this topic to enable an efficient and secure large-scale use of SCs for all application areas.

6.2. Missing Standardization and Frameworks

Established standards and frameworks for technologies can be vital and bring several advantages with them like time-saving, error prevention, and increased security. Through our analysis, we have concluded that these are largely absent in BT. So far, blockchain developers have taken a pioneering role and mostly programmed their applications in different languages without technical specifications. Thus, many unique application structures emerged that have their advantages and disadvantages as well as security risks and vulnerabilities. Standards for BT can help to foster its adoption, interoperability, make systems more secure, in particular, build trust ( Deshpande et al., 2017 ). Also, they enhance the accessibility into the general development of blockchain applications. In terms of software communication, standardized APIs can make the design of new interfaces redundant in most cases.

There is still a lot of potential in researching suitable standards and frameworks for the BT, for example, to ease the design and development of blockchain-based software, or to integrate a blockchain into research workflows. Also interesting are unified methods of how academic publishers can use this technology to improve certain of their processes and benefit from it. In our opinion, infrastructural frameworks like Hyperledger will play an even more prominent role in the future in creating a variety of new applications. One general goal of standards and frameworks must be to facilitate the entry into blockchains in order to address non-experts and break down access barriers. Altogether, both topics offer a lot of promising research possibilities, and we think they will be a cornerstone of the BT in the future.

6.3. Incentive Systems for Science

We noticed that several of the blockchain projects in our evaluation are using diverse monetary incentive systems that function through the issuance of digital coins/tokens for research contributions or specific actions like peer-reviewing. We question these incentive methods due to the current instability and speculative nature of cryptocurrencies. The worth of blockchain issued coins/tokens can vary significantly in a short period; there is also a chance of a total loss. Market development of cryptocurrencies is reviewable on Coinmarketcap. Moreover, it is not clear from where the funds are to come. Some projects propose the researchers themselves as funding bodies, but it is questionable whether they will independently reward others for their scientific contributions. Also, such a monetary incentive depends substantially on the amount of funds. Further, we see the chance that financial inducements can shift the focus of scholars from qualitative knowledge creation to a quantitative performance mentality in which they aim to achieve publications as fast as possible to profit economically.

We think there is plenty of research potential in analyzing blockchain-based incentive systems that are reliable and sustainable on the one hand and motivating for scientists on the other. In our view, exciting research questions are how to influence creative performance positively by extrinsic work stimuli, and whether BT can contribute something meaningful to that goal. A further approach is to evaluate existing incentive systems for their improvability with that technology. Currently, incentives in science mainly revolve around metrics such as the number of citations, the impact factor, and the resulting reputation. Another possibility for research is to work on inducements for the increasing quantity of micro-contributions that should also be appropriately getting acknowledged. Overall, there are several starting points worth to investigate to use the technologies' potential regarding the creation of new and enhancing of existing incentive systems for science.

6.4. Scientific Metrics

The primary information sources of scientific metrics are research platforms, for instance, ResearchGate, Mendeley 32 , Altmetric 33 , Web of Science 34 , and Google Scholar. Each of them uses its own database, which consists mainly of research profiles, publications, and their references to other research work. One exemplary metric is the number of citations that is, among other things, an element to calculate the impact factor of research papers and researchers. In that regard we compared, as short examples, the overall quantity of citations of two researchers (Jöran Beel from the Trinity College Dublin in Ireland and Melanie Swan from the Purdue University in Indiana, United States) and of the Bitcoin Whitepaper between ResearchGate and Google Scholar - date: 20th July 2019 (see Table 2 ).

Table 2 . Exemplary comparison of citation metric on two different scientific platforms.

The comparison showed significant discrepancies, and we noticed that they are even bigger with other platforms. Scientific metrics can, for instance, serve as a factor that funding bodies use for their decisions. As exemplarily demonstrated, a problem of this decision-making method is the crucial deviation of the indicators from one to another research platform triggered by utilization of different calculation formulas and a separated database per system. In concrete terms, the decision of a funding body to support a specific researcher or group can turn out differently depending on the examined network because of the non-identical values of the metrics. We think BT is a suitable possibility to noticeably improve the informative value and reliability of the scientific key figure system.

A blockchain as a shared database can provide the same data source to calculate normed metrics, so all research platforms expel identical values. Open questions are, for example, how to handle retractions in an immutable environment or who fills the infrastructure with information and manages it. However, such a working system as a fundament also opens the doors for potential novel metrics of which we think can also get usefully connected to incentive methods for researchers. Altogether, the research possibilities of the BT for scientific key figures are great because, in particular, its characteristics are suitable to build a shared database and beyond that to enhance metrics or to create new ones.

6.5. Legal Uncertainties

Some research has already been done on blockchain-based cryptocurrencies ( Ponsford, 2015 ; Gikay, 2018 ), SCs, and DAOs ( Savelyev, 2017 ; Dell'Erba, 2018 ) in connection with legal issues and topics, but there is still a lot of demand for further work and clarification ( Werbach, 2018 ). Several blockchain projects we analyzed are relying, for instance, on timestamps to prove different aspects like the existence of specific information at a certain time or want to issue certificates to verify the ownership of digital assets. A concrete example is the timestamping of a dashcam recorded video ( Gipp et al., 2016 ) that shows a car accident to confirm the moment of the crash and the authenticity of the video along with other details that can be important for the decision of a legal process. The question is, what is the legal status and acceptance when such blockchain-based evidence gets used in a lawsuit? In the case of that uncertainty, we see it as problematic that a few analyzed projects work with promises which are not juridically secured.

Further, SCs are also legally unspecified. For example, what happens if resources managed by them are no longer tangible or lost due to incorrect programming; which party is to blame and how does compensation work? SCs or DAOs can barely cover all possible real-world case constellations within their program code. In this respect, is there a technical or non-technical way to deal with unforeseen events? More questions are how juristic systems should treat SCs compared to traditional ones, and what possibilities exist to secure the contracting parties ( Savelyev, 2017 )? A general challenge is the different laws and courts in every country or state ( Dell'Erba, 2018 ), which mean that a solution that functions in a particular location is unlikely to work in all other places. So, most likely, there will not be a global consensus, but countrywide specifications would eliminate many legal uncertainties. With the increasing importance of BT and its growing adoption, we believe that juridical topics are playing a major role in the future and should be addressed to support further developments.

7. Conclusions

This paper contains an analysis about how the BT can foster open science, a review of the state-of-the-art, and an evaluation of relevant research potentials and challenges for that subject. We identified the requirements for an open scientific ecosystem and compared them with the properties of BT to verify whether they fit together. In that way, we answered our first research question and determined the technology as a reliable and appropriate infrastructure for open science. Nevertheless, we regard BT as just one building block among others and we believe that the ideas behind open science can only be implemented if all pieces are put together in a meaningful way and complement each other. Concerning our second research question, we collected and reviewed topic related literature and blockchain projects to describe the current situation. We illustrated the possibilities of the technology by many practical examples to show its capabilities for scientific workflows. Some of the analyzed projects already offer functionalities that can optimize research processes, but most of them need additional development time to implement their aimed features. For our third research question, we identified several existing challenges and research potentials. With this, we intend to draw attention to various promising and essential research topics that should get addressed to support the further development of the BT for open science.

The combination of well-known characteristics like hashing, decentralization, and immutability makes the BT unique and explains the increasing interest of science and industry in it. Due to the limited literature, open questions, and the number of projects in concept or prototype status, we noticed that the usage of blockchains in the perspective of open science is in an early development phase. Nevertheless, the technology can already make valuable contributions to that area, for example, by improving current workflows of researchers, establishing trust in technical systems and enabling new collaborations as well as mitigating existing problems. One of them is the reproducibility crisis in which BT is not a standalone solution, but in our view, a supportive part of it. But many projects need more time to mature for being beneficial. However, there is still much to do in terms of standardization, governance models, beginner-friendliness, interfaces, security and legal issues, and educational work to fully exhaust the potential of the technology.

So long as the adoption of the BT grows, we expect it to get more mature continuously. In this regard, the addressing of the identified challenges will play a vital role in the future. The current situation is comparable to a greenfield in which no specific constraints exist, and researchers have many opportunities to implement new innovative blockchain-based systems and application scenarios. Altogether, after our review, we summarize that the capabilities of the BT for open science are by far not exhausted yet. We conclude that the technology can have a significant positive impact on scientific work and its open ecosystems but that primarily depends on the technology's acceptance of the scientific community and all other associated stakeholders, which is currently unpredictable.

Author Contributions

SL has elaborated the entire content of the document, carried out the analysis, and contributed ideas to the topic. The writing of the manuscript was mainly done by SL supported by SS. MS and BG provided critical feedback and helped with the finalization.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fbloc.2019.00016/full#supplementary-material

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Keywords: blockchain, open science, infrastructure, ecosystem, review, research potentials, requirements

Citation: Leible S, Schlager S, Schubotz M and Gipp B (2019) A Review on Blockchain Technology and Blockchain Projects Fostering Open Science. Front. Blockchain 2:16. doi: 10.3389/fbloc.2019.00016

Received: 22 July 2019; Accepted: 08 October 2019; Published: 19 November 2019.

Reviewed by:

Copyright © 2019 Leible, Schlager, Schubotz and Gipp. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Stephan Leible, stephan.leible@hs-offenburg.de

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Understanding Blockchain Technology

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Bitcoin and blockchain, how does a blockchain work, public blockchain, private blockchain.

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Blockchain Technology – Prospects, Challenges and Opportunities

Muhammad Fateh Khan Sial , Assistant Professor, Department of Electrical Engineering, University of Lahore, Lahore, Pakistan

IEEE Blockchain Technical Briefs , June 2019

Discuss this topic on IEEE Collabratec

Blockchain is a digital database that is distributed across a large network. It is a sequence of interconnected blocks comprising of list of transaction records [14]. Blockchain is considered to be a public ledger in which all transactions are stored in the form of blocks. The chain expands as each new block is appended to it. Transactions cannot be altered once they are made part of blockchain. The size of database keeps on increasing as new blocks are appended to the older ones. A transaction can take place in a decentralized fashion, thus, saving cost and improving efficiency. Every time an update is made to the database on a network node, it is automatically updated across the entire network. Total number of transactions stored in a block depends on the size of each transaction and the block. Every transaction must be approved by the network nodes, each of whom verifies its validity. This block is validated using consensus algorithms where majority of network nodes approve the transaction [14].

Blockchain utilizes technologies like, distributed consensus mechanism, digital signature and cryptographic hash. The key strengths of this technology are that the records are reliable, persistent, auditable, anonymous and decentralized. Blockchain has diverse applications like crypto-currencies, online payments, digital assets, remittance, smart contracts, internet of things, security and financial services etc.

Architecture: A Block consists of a header and the body. The block header comprises of a block version, timestamp and address of the previous block etc. The block body consists of actual transaction details and the transaction counter [5]. Each block in the blockchain network points to the previous block, called ‘parent’ block, using a hash function. The very first block having no parent is referred to as ‘genesis’ block [14] .  Children of the ancestor blocks are called ‘uncle’ blocks.

Blockchain transaction process is initiated as soon as a “transaction” is requested by a network node. The request and user status are authenticated by the network using cryptographic algorithms. The verified transaction is appended with other authenticated transactions stored in a block. Once a block reaches a certain number of approved transactions, a new block is generated. After validation, the block is appended to the older blocks making it a permanent part of blockchain [2][10][11]. All the network nodes are updated with the changes every few minutes.

Characteristics: Some of the characteristics of blockchain networks are illustrated in Figure 1. It is impossible for hackers to hack these network nodes as cryptographic techniques have been deployed to secure it [1]. Each transaction is authenticated and validated using digital signature based on cryptographic algorithms [14]. The blockchain network is decentralized in nature which makes it more transparent and reliable for the storage and transfer of important data, currency, financial transaction or any valuable record [2][3]. Each transaction is validated using a timestamp which makes it possible to trace and verify previous records by accessing any network node. It helps in improving transparency of data stored on the network [14]. Each user interacts with the network with a generated address. A certain amount of user privacy is preserved as there is no central entity that stores user’s private information. It is possible to perform anonymous transactions on the blockchain network. It only requires the network address of the receiver to perform the transactions [11].

A transaction can be performed between any two peers directly without interference of any central entity. It results in reduced operation and development cost of servers. Any falsification in data can be detected easily as each broadcasted block will be validated by other network nodes. The record cannot be altered without the consensus of group members, which makes blockchain transactions more reliable and persistent. The network nodes verify transactions collectively. Any financial transaction made on the network is confirmed and secured using cryptographic algorithms. Once a transaction has been verified by the network, it is placed in a block in a way that newer blocks are placed under previous blocks of financial transactions.

Being a shared database, details of the financial transaction are visible to all nodes. So, the network is transparent and requires trust of the users. Financial transactions can be made without the need of third-party interference. There is no central point of failure, so the network keeps on running even if any of the nodes leaves the network, making all the data accessible to users all the times. Records in a blockchain are immutable and will be saved for unlimited time [1][2][3][11].

Figure 1. Blockchain characteristics [2]

Types of Blockchain: A blockchain network has three types: public, private and consortium [2][4].

• Public Blockchain: These networks allow anyone to join the network and execute transactions visible to every network user. There is no trust relationship among the network users before joining the network. Transaction can be verified by any node. All nodes participate in the transaction consensus process. Bitcoin and Ethereum belong to the class of public blockchain [11].
• Private Blockchain: These networks are permission based. These are also referred to as “permissioned ledgers” and are constructed using Hyperledger Fabric which is hosted by Linux Foundation. The digital records can be encrypted and are visible only to authorized users, thus privacy requirements of the data are fulfilled [3][4][5]. The main difference between private and public networks is user verification and authentication mechanism [3]. In public blockchain networks, there is no trust relationship among the network nodes. Before any transaction can be performed, there is computing overhead involved in user validation which increases the time for each transaction. Contrarily, in private blockchain networks, permission based trust is involved before any transaction is made. It significantly reduces the computation overhead for running the authentication and validation algorithms. Consequently, thousands of transactions can be performed per seconds on private blockchain networks as compared to a few transactions per second in public networks. The blockchain network can be owned by a single network provider or multiple consumers. The owner of the network determines whether it is public or private in nature [3][4].
• Consortium Blockchain: In consortium networks, block authentication is performed by a set of specific nodes. It is categorized as semi private and permissioned blockchain. It is a partially centralized system controlled by a few selector nodes, contrary to public blockchain (decentralized) and private blockchain (centralized). Network nodes having authority can configure the data in blockchain to be public or private. R3CEV and Hyperledger are examples of Consortium Blockchain networks [11].

Challenges: There are a few challenges associated with the blockchain networks [2][9]. There is huge storage requirement as the validation process involves the whole blockchain. Only a few transactions can be performed per second due to fixed block size which in turn causes increased transaction delays and high transaction fee. If the block size is increased, it will cause additional delay in block propagation. Moreover, it is possible to generate fake blocks by the network nodes or generate transactions that are reverse confirmed. Rapid generation of blocks is possible by increased power consumption, resulting in legitimate blocks not being able to get their share of blockchain network resources. An important challenge of blockchain networks is the energy consumption. These transactions consume huge amount of energy. It is estimated that each Bitcoin transaction consumes 80,000 times more energy as compared to a credit card transaction.

Applications: This technology not only benefits crypto-currencies but also many different industries that need to store and manipulate huge amounts of data. Blockchain technology has the potential to support the field of financial, public and social services like land record management, asset management, educational services, energy conservation, citizen registration systems, patient management, taxations system, security and privacy enhancement of mobile devices and associated services [14]. Here are some of the industries that employ blockchain technology to improve their operations: banking, cybersecurity, academia, marketing and advertising, supply-chain management, ecommerce, voting, supply-chain networks, finance, asset management, healthcare, real estate, Internet of Things, government record keeping and health industries etc. [2][5]. An overview of blockchain areas of applications and associated services is listed in Table 1.

In general, blockchain technology is applicable for the following conditions [12],

• Digitization of assets to provide data driven business models.
• Digitization of processes and transactions among business partners.
• Provision of immutable records of transactions and assets.
• Provision of decentralized, permanent and secure data storage.

Table 1: Blockchain applications and services [13]

Future directions: Leading platforms that are driving innovation in this area are Hyperledger, R3 and Ethereum [3]. These open source communities are at the foundation of the Blockchain platform technology “pyramid”. Multiple horizontal and vertical platforms are being developed by IT vendors like IBM, Microsoft, Oracle, SAP etc. These companies are developing horizontal Blockchain platform based on the three open source technologies, mentioned above, at the base of the pyramid. Subsequently, this middleware serves as the middle layer of the pyramid. Customized solutions for different Blockchain verticals are being developed by different consulting companies like KPMG, Accenture and Cognizant etc. These system integrators and consulting companies constitute the top of the pyramid [3].

The field of Blockchain technology is at the nascent stage. It is anticipated that the enterprises will extend their existing IT systems with Blockchain based systems to test its functionality and upgrade internal business processes and models subsequently. However, it will take time for the industry to appreciate the real benefits of this technology and the value it could bring to an organization, before the core IT functions are completely transferred to this technology.

References:

[1] Mazonka, Oleg. Blockchain: Simple Explanation. Journal of Reference, 29 December 2016.

[2] D. Puthal, N. Malik,  S. P. Mohanty , E. Kougianos, and G. Das.  Everything you Wanted to Know about the Blockchain : Its Promise, Components, Processes, and Problems. IEEE Consumer Electronics Magazine, Volume 7, Issue 4, July 2018, pp. 06-14.

[3]  Kaladhar Voruganti . Networking-for-nerds-blockchain-technologies [online] Available:  https://blog.equinix.com/blog/2018/01/15/networking-for-nerds-blockchain-technologies/

[4] V. Buterin. On public and private blockchains 2015 [online] Available:  https://blog.ethereum.org/2015/08/07/on-public-and-private-blockchains/ .

[5] Z. Zheng, S. Xie, H. Dai, X. Chen, and H. Wang. An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends. Proceedings of the IEEE International Congress on Big Data, pp. 557-564, 2017.

[6] R. Grinberg. Bitcoin: An Innovative Alternative Digital Currency. Hastings Science & Technology Law Journal, Vol. 4, pp. 159-208, 2012.

[7] S. Barber, X. Boyen, E. Shi, and E. Uzun. Bitter to better -- How to make bitcoin a better currency. Proceedings of the International Conference on Financial Cryptography and Data Security, pp. 399-414, 2012.

[8] S. Nakamoto. Bitcoin: A Peer-to-Peer Electronic Cash System. [Online] Available:  https://bitcoin.org/bitcoin.pdf . Last visited 15 August 2018.

[9] N. Popper. There is Nothing Virtual About Bitcoin's Energy Appetite. The New York Times, 21st Jan 2018. [online] Available:  https://www.nytimes.com/2018/01/21/technology/bitcoin-mining-energy-consumption.html Last Accessed on 15 August 2018.

[10] X. Li, P. Jiang, T. Chen, X. Luo, and Q. Wen. A Survey on the Security of Blockchain Systems. Future Generation Computer Systems, 2017, doi =  https://doi.org/10.1016/j.future.2017.08.020 .

[11] Iuon-Chang Lin, Tzu-Chun Liao. A Survey of Blockchain Security Issues and Challenges. International Journal of Network Security, Vol.19, No. 5, pp. 653-659, Sept. 2017.

[12] Thomas Mueller. Three simple steps to find the ultimate answer to the question: “ When do I need Blockchain for my business?”. [Online] Available:  https://medium.com/evan-network/three-simple-steps-to-find-the-ultimate-answer-to-the-question-when-do-i-need-blockchain-for-my-cd794ae10c40

[13] Melanie Swan. Blockchain-Blueprint for a new economy. O’Reilly, First edition, Feb. 2015.

[14] Zibin Zheng, Shaoan Xie, Hong-Ning Dai, Xiangping Chen, Huaimin Wang. Blockchain challenges and opportunities: A survey. International Journal of Web and Grid Services, pp. 352- 375, Vol. 14, No. 4, 2018.

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Open Access

Peer-reviewed

Research Article

A look into the future of blockchain technology

Roles Conceptualization, Data curation, Investigation, Methodology

Affiliation Groupe ALTEN, France

Contributed equally to this work with: Francesco Fontana, Elisa Ughetto

Roles Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, Italy

Roles Conceptualization, Investigation, Methodology, Project administration, Supervision, Validation, Writing – original draft, Writing – review & editing

Affiliation Politecnico di Torino & Bureau of Entrepreneurial Finance, Corso Duca degli Abruzzi 24, Turin, Italy

• Daniel Levis, 
• Francesco Fontana, 
• Elisa Ughetto

• Published: November 17, 2021
• https://doi.org/10.1371/journal.pone.0258995
• Reader Comments

In this paper, we use a Delphi approach to investigate whether, and to what extent, blockchain-based applications might affect firms’ organizations, innovations, and strategies by 2030, and, consequently, which societal areas may be mainly affected. We provide a deep understanding of how the adoption of this technology could lead to changes in Europe over multiple dimensions, ranging from business to culture and society, policy and regulation, economy, and technology. From the projections that reached a significant consensus and were given a high probability of occurrence by the experts, we derive four scenarios built around two main dimensions: the digitization of assets and the change in business models.

Citation: Levis D, Fontana F, Ughetto E (2021) A look into the future of blockchain technology. PLoS ONE 16(11): e0258995. https://doi.org/10.1371/journal.pone.0258995

Editor: Alessandro Margherita, University of Salento, ITALY

Received: June 1, 2021; Accepted: October 9, 2021; Published: November 17, 2021

Copyright: © 2021 Levis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1 Introduction

Over the last few years, the hype and interest around blockchain technology have consistently increased. Practitioners from many industries and sectors have joined an open, yet mainly unstructured, discussion on the potential disruptive capabilities of this newly born technology [ 1 – 3 ]. In principle, the size of the phenomenon could be huge, with latest estimates predicting blockchain to store, by 2025, the 10 per cent of the world’s GDP (about $88tn in 2019) [ 4 ]. However, the complexity of the technology itself and the difficulties in assessing its impact across the different application fields have prevented the social, industrial and scientific communities to agree upon a shared vision of future blockchain-based scenarios. Very fundamental questions are still to be answered. Which blockchain-enabled applications will see the light in the next few years? Which industrial sectors will be mainly affected? How will companies react to potential industry-disruptors? How will the current societal paradigm shift? Which role will policy makers play in enhancing this new paradigm?

Despite the great and undoubted technological innovation linked to this technology, uncertainties and speculation on the potential scenarios still animate the industrial and scientific dialogue [ 5 ]. In particular, it is not yet clear which applications will see the light, and, eventually, what effects these changes will have at a societal level.

In this paper, we use a Delphi approach to investigate whether, and to what extent, blockchain-based applications will affect firms’ organizations, innovations and strategies by 2030, and, consequently, which societal areas will be mainly affected. With this methodology, we aim at reaching experts’ consensus to gain new insights and assess the likelihood about the future of the technology. This is a relevant issue, as blockchain technology applications cover a wide spectrum of areas. Blockchain can be applied vertically within an industry (e.g. disrupting its supply chain) or horizontally across different industries or within single companies (e.g. modifying the internal structures and the modus operandi of the different company functions). Given the number of potential applications and the complexity of the technology, stakeholders are divided into skeptics, who believe the technology is still too immature to become a paradigm in the near future, and enthusiasts, who instead believe that this radical innovation will disrupt many industries and completely change business models and people’s behaviors, like internet did during the 90s.

The literature on blockchain is also widely fragmented. Different works have investigated possible blockchain applications within specific domains, such as finance [ 6 – 8 ], logistics [ 9 ], healthcare [ 10 , 11 ] and education [ 12 ]. However, a holistic approach on possible blockchain-enabled future scenarios is still missing. To our knowledge, the only contribution in this direction is the one by White [ 13 ], who explores blockchain as a source of disruptive innovation exclusively with regard to the business field. We depart from his work to adopt a much wider perspective in this study. In fact, our aim is to obtain a deep understanding on how the adoption of this technology in Europe will lead to changes over multiple dimensions, ranging from business to culture and society, policy and regulation, economy and technology. Thus, our research aims at exploring if a convergence between the two divergent perspectives on blockchain can be found, bringing together experts currently working on blockchain projects to explore the possible changes that the technology will bring to the society by 2030.

Our study outlines an overall agreement among experts that the blockchain technology will have a deep impact on multiple dimensions. In the near future people will likely start using and exploit the blockchain technology potential, without really knowing how the technology behind works, in the same way as they send emails today, ignoring how the digital architecture that allows to exchange bytes of information works. Policy makers and governments will play a crucial role in this respect, by enabling productivity boosts and competitive gains from the companies operating under their jurisdictions. As such, a tight and cooperative relationship between industrial actors and regulatory bodies will be extremely important and auspicial. To this aim, it will be of key importance for all players to understand the real competitive advantage that blockchain can bring to their own industry and market.

This work aims at contributing to the raising blockchain literature by offering a holistic view on possible blockchain-enabled future scenarios in Europe, and to investigate which of the proposed scenarios is more likely to occur. As widely agreed by the academic literature, technological developments dictate the speed and pace at which societies change [ 14 ]. Under this assumption, technological forecasting appears to be a method of fundamental importance to understand “ex-ante” the potential development of technological changes, and their impact on different societal aspects [ 15 ]. Foreseeing future technological trends could help society in understanding possible future scenarios, thus contributing to a better knowledge of the new paradigms our society is heading towards. The work is structured as follows. Section 2 provides an overview on the main research streams upon which this work is based. Section 3 presents the methodology. Results are described in Section 4 and Section 5 concludes the work.

2 Background literature

2.1 the blockchain technology.

As defined by Crosby et al. [ 3 ] a blockchain can be conceptualized as a shared and decentralized ledger of transactions. This chain grows as new blocks (i.e. read transactions or digital events) are appended to it continuously [ 16 , 17 ]. Each transaction in the ledger must be confirmed by the majority of the participants in the system [ 3 , 18 – 21 ]. This means for the community to verify the truthfulness of the new piece of information and to keep the blockchain copies synchronized between all the nodes (i.e. between all the participants to the network) in such a way that everybody agrees which is the chain of blocks to follow [ 19 ]. Thus, when a client executes a transaction (e.g. when it sends some value to another client), it broadcasts the transaction encrypted with a specific technique to the entire network, so that all users in the system receive a notification of the transaction in a few seconds. At that moment, the transaction is “unconfirmed”, since it has not yet been validated by the community. Once the users verify the transaction with a process called mining, a new block is added to the chain. Usually, the miner (i.e. the user participating to the verification process) receives a reward under the form of virtual coins, called cryptocurrencies. Examples of cryptocurrencies are Bitcoins, Ether, Stellar Lumens and many others. Virtual coins can then be used on the blockchain platform to transfer value between users [ 17 – 19 ].

Thanks to a combination of mathematics and cryptography, the transactions between users (i.e. exchange of data and value), once verified by the network and added to the chain, are “almost” unmodifiable and can be considered true with a reasonable level of confidence [ 17 , 19 , 22 ]. These attributes of the technology make it extremely efficient in transferring value between users, solving the problem of trust and thus potentially eliminating the need of a central authority (e.g. a bank) that authorizes and certifies the transactions [ 7 , 23 , 24 ].

The technology can be easily applied to form legally binding agreements among individuals. The digitalized asset, which is the underlying asset of the contract, is called token. A token can be a digitalized share of a company, as well as a real estate property or a car. Through the setting of smart contracts (i.e. digitalized contracts between two parties), the blockchain technology allows users to freely trade digital tokens, and consequently to trade their underling physical assets without the need of a central authority to certify the transaction (OECD, 2020).

2.2 Blockchain technology applications

The academic literature has investigated a wide range of possible blockchain applications within specific domains, such as finance [ 6 – 8 ], logistics [ 9 ], healthcare [ 10 , 11 ] and education [ 12 ].

As mentioned, one of the undoubted advantages of the blockchain technology is the possibility to overcome the problem of trust while transferring value [ 25 ]. Not surprisingly, the technology seems to find more applications in markets where intermediation is currently high, like the financial sector, and in particular the FinTech sector, that has recently experienced a consistent make-over thanks to the diffusion of digital technologies [ 7 , 26 , 27 ]. The implementation of the blockchain technology in the financial markets could provide investors and entrepreneurs with new tools to successfully exchange value and capitals without relying on central authorities, ideally solving the problem of trust. This is among the reasons why many observers believe that the blockchain would become a potential mainstream financial technology in the future [ 28 ]. Blockchain represents an innovation able to completely remodel our current financial system, breaking the old paradigm requiring trusted centralized parties [ 6 – 8 ]. With new blockchain-based automated forms of peer-to-peer lending, individuals having limited or no access to formal financial services could gain access to basic financial services previously reserved to individuals with certified financial records [ 29 ]. Indeed, blockchain technology can provide value across multiple dimensions, by decreasing information asymmetries and reducing related transactional costs [ 30 ]. Initial coin offerings (ICOs) represent one of the most successful blockchain-based applications for financing which has been currently developed. Virtual currencies like Bitcoins can disruptively change the way in which players active in the business of financing new ventures operate [ 7 , 30 – 33 ]. Through an ICO, a company in need of new capital offers digital stocks (named token) to the public. These digital tokens will then be used by investors to pay the future products developed by the financed company [ 30 , 34 , 35 ]. ICOs represents a disruptive tool: entrepreneurs can now finance their ventures without intermediaries and consequently lower the cost of the capital raised [ 31 , 36 ]. However, some threats coming from the technology adoption can also be identified, as blockchain can also lead to higher risks related to the lower level of control intrinsically connected to the technology, especially in the case of asymmetric information between the parties involved.

Disintermediation plays a key role in the healthcare sector as well, where blockchain has recently found numerous applications. Indeed, many players currently need to exchange a huge amount of information to effectively manage the whole sector: from hospitals, to physicians, to patients. The ability to trustfully exchange data and information becomes of undoubted value in this context [ 10 , 11 ]. It should not be difficult to envision blockchain applications in other fields as well. In every sector in which information, value, or goods are supposed to flow between parties, blockchain can enable a trustful connection between the players, with the need of a central body entrusting the transaction. Within supply chain, it can increase security and traceability of goods [ 9 , 37 ]. Within education, it can help in certifying students’ acquired skills, reducing, for example, degree fraud [ 12 ]. To conclude, a recent work from Lumineau et al. [ 38 ] highlights possible implications of the technology in the way collaborations are ruled and executed, shading light on new organizational paradigms. Indeed, the authors show how the intrinsically diverse nature of the technology could strongly affect organizational outcomes, heavily influencing and modifying (possibly improving) the way in which different entities cooperate and collaborate.

3 Research methodology

3.1 forecasting technique: the delphi method.

In the past decade, an increasing number of forecasting techniques has been employed in the academic literature to predict the potential developments induced by technological changes. In particular, the Delphi method, whose term derives from the Greek oracle Delphos, is a systematic and interactive method of prediction, which is based on a panel of experts and is carried out through a series of iterations, called rounds. Many academic works have adopted this method since its development [ 14 , 39 – 44 ]. As the core of the Delphi approach, experts are required to evaluate projections (representations of possible futures) and assess their societal impact and the likelihood that they will occur within a specific time horizon.

While the majority of forecasting methods does not account for the technological implications on the social, economic and political contexts, the Delphi technique allows subjective consideration of changes in interrelated contexts [ 45 ]. Many different variants of the Delphi methodology have been developed according to the needs and goals of each research. For the purpose of this research, we decided to follow the four-steps procedure suggested by Heiko and Darkow [ 46 ] ( Fig 1 ).

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• TIFF original image

https://doi.org/10.1371/journal.pone.0258995.g001

The first step of the method requires to develop and envisage projections and possible scenarios that might arise through the adoption of the technology. These projections must be short, unequivocal, and concise [ 14 ]. This phase requires researchers to deeply understand the technology by analyzing the existing literature, attending courses and workshops and conducting a number of face-to-face interviews with experts ( Fig 2 ). Once the insights are gathered, the results are synthetized in future projections that will help develop the survey. The second step consists in presenting the study to the panel of selected experts who will take part in the first round of the survey. The main challenge during this phase is to select an appropriate panel of experts and maintain their commitment and response rate. The third step consists in a statistical and quantitative analysis of the answers received and in the selection of the second-round scenarios that experts will need to evaluate again. Through the analysis of the second round of answers, updated scenarios are developed adding to the projections the qualitative and quantitative insights provided by the research. The ultimate goal of this iterative process is to reach consensus among the experts on the scenarios that are most likely to happen in the future.

https://doi.org/10.1371/journal.pone.0258995.g002

3.2 Formulation of the Delphi projections

The formulation of the projections represents a key aspect of the methodology and requires a particular attention and effort. In this phase, the projections that are later tested by the panel of experts are generated. Vagueness and inaccuracy might generate confusion in experts, leading to less meaningful results. To avoid this situation, we developed the projections by means of triangulation: literature review, interviews with experts and participation to workshops and conferences. The analysis of the literature on blockchain technology (and its benefits) allowed us to understand which industries and businesses will be mainly impacted by the technology.

We chose 2030 as a time horizon for the generation of the scenarios. This is a recommended time span for a Delphi study, since a superior period would have become unmanageable to provide relevant advice for strategic development. As reported in Table 1 , projections span among different areas. To the scope of the work, i.e. to grasp a holistic view of the most likely scenarios, it was necessary to investigate a number of multiple dimensions. Projections are related to socio-cultural, policy and regulations, economic, technological and business aspects. As it can be noticed, projections are all structured in the same way, to facilitate their understanding by experts.

https://doi.org/10.1371/journal.pone.0258995.t001

3.2.1 Interviews with experts.

Twelve blockchain experts were interviewed among academics, startups’ founders and professionals working in consultancy firms, banks and legal institutions. The selection of the experts was made in order to get different points of view and a high level of expertise, as provided by the Delphi method guidelines. We conducted interviews that took between thirty and forty-five minutes on average, according to the interviewee’s availability. Each single interview was tailored for each participant by providing guidelines and reflection tips to encourage discussion. However, a certain degree of freedom was given to the expert to allow his/her spontaneous contribution and to gain some original insights that helped in the final design of the future scenarios. Some common aspects were discussed in all interviews generating redundancy and repetition of already emerged scenarios (e.g. ICOs, business model evolution, security and utility tokens, and legal issues). This is one of the reasons why twelve interviews were considered to be sufficient for the purposes of our research.

3.2.2 Conferences.

One of the authors attended three main events in order to strengthen the knowledge about blockchain and have a broader view of its implications in different fields and industries: one in Milan and two in Paris. Of particular notice, the Community Blockchain Week, a blockchain tech-focused initiative organized voluntarily by actors engaged into the technology and with the will and vision to spread the knowledge among citizens. Thanks to various workshops and speeches during the week, it was possible to dive deeper into many aspects of the technology, as well as to meet some knowledgeable experts of various fields, some of which agreed in participating to the research. The event was extremely useful not only to understand how the technology is evolving, but also to see how the community engages itself to spread the knowledge in order to generate more and more interest around it.

3.2.3 Desk research.

We performed desk research to formulate the initial set of projections. Through the survey of the literature, we gained a comprehensive view of all the potential scenarios of the technology. The analysis of consulting companies’ reports also offered a broader vision of future scenarios, thanks to their strategic rather than technical approach [ 1 , 2 ]. This process led to identify 76 projections that represented the basis for a reflection during the expert face-to-face interviews. After screening the relevant articles and reports, a first filtering of the identified 76 projections was made in order to dismiss redundant or incomplete projections, and to keep only the most complete and varied ones. This process reduced the number of projections to 33 and to 20 after the review of two experts.

3.3 The Delphi projections

The formulation of the projections represents the most sensitive part of the research since it influences the whole study. A detailed analysis was carried out in order to avoid mistakes and confusion. In order to facilitate the respondents filling the questionnaire and to avoid any kind of ambiguity, an introduction explaining the meaning of the terminology used in the questionnaire was presented before starting the survey. The developed scenarios were broken down into six macro categories (the same as proposed by Heiko and Darkow [ 46 ]) to guarantee a more complete and systemic view of how the blockchain ecosystem and community can change and shape the future. The choice of 20 projections to be evaluated by experts is in line with prior studies exploiting the Delphi method [ 46 , 47 ]. Parente and Anderson-Parente [ 47 ] have proposed to limit the number of Delphi questions (e.g. to 25 questions) in order to guarantee a high response rate and properly filled-in questionnaires, including only closed answers. We decided to add the possibility to comment the given answers in order to gather additional qualitative data to improve the quality of the results, in line with the methodology proposed by Heiko and Darkow [ 46 ].

3.4 Selection of the panel of experts

As blockchain experts that took part to the survey, we selected individuals working in companies and institutions on the basis of their experience and knowledge of the field. Following Adler and Ziglio [ 48 ] and Heiko and Darkow [ 46 ] four requirements for “expertise” were considered:

• knowledge and experience on blockchain technology;
• capacity and willingness to participate to the Delphi study;
• sufficient time to participate to the Delphi study;
• effective communication skills.

A minimum panel size of 15–25 participants is often required to lead to consistent results. In our case, a panel of 35 experts was reached for the first round. For the reliability of the study the panelists were selected with different backgrounds and profiles. To be aligned with the European focus of the study, we considered experts working in twelve European countries, being France and Italy the ones with the highest number of respondents. The panel characteristics are reported in Figs 3 , 4 and 5 .

https://doi.org/10.1371/journal.pone.0258995.g003

https://doi.org/10.1371/journal.pone.0258995.g004

https://doi.org/10.1371/journal.pone.0258995.g005

3.5 Execution of the Delphi surveys

In line with the methodology proposed by Heiko and Darkow [ 46 ], two rounds of surveys were executed. We decided to carry no more than two rounds because participating to a Delphi study requires a lot of effort and is a time-consuming task for panelists. By limiting the rounds to two, we reached a sufficient number of respondents that led to have valuable results and consistent conclusions. Moreover, since for each scenario the possibility to include a qualitative argumentation was included, the smaller number of iterations worked as a stimulus for the experts to explain the reasons of their quantitative answers.

The survey was carried out following the standards of the Internet-based Delphi, also called e-Delphi [ 39 , 40 ]. Giving the possibility to respondents to answer digitally allowed experts to be more flexible in responding to the survey, ensuring a greater participation. The way the questionnaire was structured was exactly as the e-Delphi website suggests, but for practical reasons we edited the survey using Google Form. Other standards, such as the real-time Delphi solution proposed by several studies [ 14 , 42 , 43 , 49 ] could have led to a better comparison among experts, but would have likely caused more withdraws to the survey.

3.5.1 First round.

In the first round of the survey, the experts assessed the expected probability and impact of the twenty outlined projections. Some Delphi studies [ 50 , 51 ] include a third factor that helps to assess the desirability of a scenario (i.e. how much an expert is in favour of the realization of a prediction). However, we decided not to include this last aspect to make the questionnaire lighter and faster to be filled in, and to reduce drop-outs ( Table 2 ).

https://doi.org/10.1371/journal.pone.0258995.t002

Impact, evaluated at the industry level, was measured on a five-point Likert scale [ 52 ]. Since there is not a general consensus among experts regarding the number of points the scale should have, and due to the general nature of the scenarios, we preferred to use a five-point Likert scale. The corresponding probabilities are: 0%, 25%, 50%, 75% and 100%. Gathering quantitative data allowed to perform a first set of analyses based on descriptive statistics (e.g. mean, median and interquartile range-IQR). We used qualitative data, instead, to build the final scenarios during the fourth step of the forecasting technique. Even though the literature regarding the Delphi method does not suggest a standardized way to analyze consensus, central tendency measures, such as median and mean values, are useful to grasp a first understanding and are frequently accepted and adopted ( Table 3 ). Scenarios with an IQR equal or lower than 1.5 were considered as having reached an acceptable degree of consensus. It should be noticed that most of the projections that achieved the highest probability, having a median value of 75% achieved also the consensus, i.e. IQR below 1.5. This was the case for projections 3, 4, 8, 9, 10, 13, 15, 19, 20.

https://doi.org/10.1371/journal.pone.0258995.t003

These results show that it was easier for experts to find a consensus over the projections that resulted as very likely to occur. Only projection number 18 achieved a high probability score but could not reach a consensus.

3.5.2 Second round.

During the Delphi’s second round only the projections with an IQR above 1.5 (i.e. which did not reach consensus in the first round) were tested. In order to allow the respondents to easily understand the answers that the panel gave as a whole in round one, for each projection a quantitative report was provided. This report was made of a bar chart with the distribution of the first round’s answers and the correspondent qualitative details, i.e. some of the argumentations provided by some of the panelists. Experts were asked to reconsider the likelihood of occurrence of the projections number 1, 5, 7, 11, 12, 14 and 18. The second round was again structured using Google Form. Following the Delphi’s approach, we did not ask again to estimate the impact for each projection, since this would have presumably been not subject to any change. Moreover, we decided to leave the opportunity to offer again some qualitative comments in support of the answers for a better analysis of the results. The number of experts who successfully completed the second round of the survey dropped to 28, i.e. the 80% of the experts that completed Round 1 and 56% of the selected initial panel. Again, we evaluated the central tendency measures for the projections tested during the second round ( Table 4 ).

https://doi.org/10.1371/journal.pone.0258995.t004

In order to provide a more effective and structured analysis of the results, we first report the final summary table of the Delphi survey and then describe the insights obtained from the analysis. It has to be noticed that Table 5 reports quantitative data only, while during the survey qualitative data were collected as well. In presenting the results of this research, both quantitative and qualitative data are used to provide the best possible picture of what the blockchain-based future will look like. Alongside with standard statistics, we build on qualitative insights obtained during the interviews carried on with experts.

https://doi.org/10.1371/journal.pone.0258995.t005

Firstly, it is interesting to analyze which projections, out of the initial 20, reached a significant consensus (IQR <1.5 after the two rounds of the surveys) and were given a high probability of occurrence by the experts. We can summarize the findings in this domain around three major axes: efficiency, security, and innovation.

By 2030, it will be easier, faster and leaner to exchange value and data among users, institutions and countries. Efficiency will boost and uncover innovation potential within companies and societies if these latter will be able to exploit such a new opportunity. Policies will be a necessary pre-requisite for companies to be able to build a competitive edge globally. From this perspective, the capability of central governments to spur innovation with lean and flexible regulations will be a key driver in explaining the ex-post productivity differential among companies belonging to different countries. From the interview with an investment banker part of the BPCE French group (one of the largest banks in France), it emerged how efficiency is often hampered by the lack of an equally efficient regulation. To provide the reader with an interesting example, in 2018, Natixis, the international corporate and investment banking, asset management, insurance and financial services arm of BPCE, entered the Marco Polo consortium, an initiative born to provide a newly conceived trade and supply chain finance platform, leveraging Application Programming Interfaces (APIs) and blockchain technology. Many other leading banks joined the consortium as well. However, as highlighted by the investment banker, the main limiting factor of the consortium, strongly hampering its efficiency and ability to provide a competitive edge, was the “old-style” bureaucracy linked to it. Although transactions were in principle to be executed smoothly, a bulk of legal paperwork was required to approve them formally. In this case, it appears evident that technology often runs faster than policy, consistently lowering its potential. Interestingly, this view is also shared by regulatory bodies. An experienced lawyer and notary, also member of a panel of experts elected by the Italian government to define the national strategy on blockchain, highlighted that, sometimes, regulators working on blockchain-related policies are trying to adapt existing regulations to the new paradigm. Due to the intrinsically different nature of the technology, this could represent a wrong approach. At the same time, building a new set of policies from scratches could represent a challenging task. From this perspective, projections 4 and 5 confirm this insight: policy and technology should come hand in hand to synergically boost productivity. The three projections reached consensus after the two rounds and were assigned a high probability of occurrence. Overall, it is evident that regulatory aspects linked to the adoption of this new technology shall not be underestimated.

As previously mentioned, security, and specifically cybersecurity, is another dimension around which blockchain could bring consistent advantages, as projections 3, 10, 11 and 15 suggest. On this specific aspect, we interviewed a project leader of the World Economic Forum who previously worked for the United Nations for more than ten years. She dealt specifically with digital regulations, justice, and cybersecurity, and in the last three years before the interview, she specifically worked on blockchain implications and how the technology could be implemented in existing ecosystems. Thanks to her experience in the domain, she clearly explained how the blockchain represents a meaningful technology to avoid cyberattacks to sensitive data and digital files. In her opinion, the avoidance of a single point of failure is the main reason behind a possible blockchain adoption over the next years, since cyberattacks are becoming more frequent and dangerous and related costs for companies are exponentially increasing (e.g. 2020 has been a record year for cyber attacks). Consequently, companies will be increasingly investing in distributed ledgers as a form of contingency budget to lower the cybersecurity risk and its related cost. Given the centrality of data in today’s businesses, serious attacks and loss of data could represent a serious threat to business long-term sustainability.

The third relevant aspect on which blockchain will have a strong impact is, not surprisingly, innovation. Although regulation could represent a non-negligible limiting factor, experts foresee many sectors to be impacted by the technology adoption. For example, the financial sector could be heavily affected by this new paradigm. Particularly, companies’ capital structures and their strategic interlink with business models will drive a differential competitive power. Most likely, enterprises will have to rethink their business models to account for the possibility to digitize/tokenize their assets (Projections 8 and 18). The capability in flexibly adapting their service offerings to the new opportunity and the ability to raise, and re-invest, new capitals will shape the global competition landscape across different industrial sectors and geographies. From one side, blockchain will enable new strategic decisions, from the other side, it will be of fundamental importance to build technological capabilities to enable these decisions. The underlying technology behind transactions, equity offering and equity share transfers will most likely be the blockchain (Projections 13 and 16). Disintermediation and the ability to exchange value, information, and data trustfully without a central authority will enable a new way of funding and cooperation on open-source projects (Projection 19). Most likely, people will refer to blockchain systems as they now refer to browsers such as Chrome, Firefox or Internet Explorer. Many blockchains are already available and are constantly improved and developed, and it is foreseeable that this will remain the case in the future. Users will just need to know the characteristics that a blockchain provides to choose the most suitable one for their business and purposes. Blockchain-based systems will require new skills and knowledge that developers and engineers will need to develop. Big efforts will be needed to make the blockchain more and more user friendly and attractive for those who just want to benefit from the immutability, traceability, and security that it intrinsically brings. At the time of the writing and in line with the Abernathy and Utterback model [ 53 ] many players are currently investing and innovating on blockchain to provide services that will satisfy the new market needs.

The opportunity for people to deal freely will in fact generate opportunities that were unforeseeable before. Self-enforcing smart contracts (Projection 20) will let parties to buy and sell products or to rent them with pay-for-use schemes in an automated way, the digitization of shares and assets will allow companies to raise capital in new ways, without the need to rely on banks, venture capitals or traditional IPOs. Indeed, it is important to understand how the digitization of assets can challenge existing investments and the funding industry represented by traditional private equity firms and banks. Blockchain could allow the creation of platforms for the issuance of traditional financial products on a tokenized nature, making it easier, more transparent and cheaper to manage and access these tools for everyone, including both individual savers and SMEs. Two different types of companies can and will operate in the market: those which have blockchain at their core since their foundation, and those which have (or will have) to embark in a digital transformation process to reconvert themselves into blockchain-based enterprises. In both cases, companies are investing to get a competitive advantage over competitors, betting on the technology that is promising to reduce costs and increase efficiency. Once a dominant design in product and services will be achieved, companies that took a different path will likely exit the market, letting firms following the dominant design to gain market shares.

To conclude and to conceptualize the insights we obtained from both quantitative and qualitative data, we derived four scenarios that we organized in a matrix framework, reported in Table 6 . The framework was built around two main dimensions: on one hand the digitization of assets, and on the other hand the change in business models. The proposed framework leads to the identification of four quadrants: scenarios which envision both the digitization of assets and business model changes and scenarios which do not foresee neither of these two changes. These four main development scenarios were completed and analyzed in the light of the conducted interviews and of the quantitative and qualitative data gathered through the Delphi survey. Each quadrant was given a label: Internal Processes, Flow-less Coopetition, Suppliers Potential and Investment Opportunities. When discussing the quadrants, we try to highlight which of the three improvement areas previously identified (efficiency, security, and innovation) are exploited in the discussed scenario.

https://doi.org/10.1371/journal.pone.0258995.t006

To derive relevant insights from the framework, it is useful to start from the bottom left quadrant, Internal Processes. This name was chosen to highlight the absence of any particular evolution for the company at a strategic level through the blockchain adoption. In this case, it is conceivable to use the technology to incrementally improve firms’ operation performances. Blockchain’s main benefits are to increase traceability of transactions and guarantee their immutability. All these characteristics adopted on today’s processes will result in an automation of routine business functions, such as settlements and reconciliation, customs clearance, heavy payments, invoicing, and documentation, boosting operational efficiency and cost performance. In this scenario, security and efficiency will see a consistent improvement.

The top-left scenario shows instead a different perspective, by considering a broader adoption of blockchain that generates new cooperative business models among different stakeholders, potentially even among competitors. This is why it is called Flow-Less Coopetition. In this case, the benefits of blockchain will help at generating a more democratic ecosystem in terms of information. Those actors that base their business models on information asymmetry, having access to key information before others, will need to revisit their business models if they want to stay competitive. It is of interest to notice how big financial institutions, traditionally competing, are now exploring potential collaboration models in the light of this new technology (e.g. JP Morgan Chase, Morgan Stanley). This quadrant envisages an advance in all three blockchain-enabled dimensions: efficiency, security, and innovation.

The bottom-right scenario, called Suppliers Potential, highlights how, thanks to the digitization that blockchain allows, many actors could jump in the market providing solutions to those companies that would like to benefit from the advantages of digitizing their assets, but are lacking means and competences to internally develop them. Those companies would rather outsource the development of blockchain-based solutions. For this reason, the potential for the creation of a remunerative B2B market exists. Even though there are already protocols that are leaders in the market (Hyperledger Fabric and Ethereum), new solutions with different configurations will likely be needed to support different industries and use case solutions. As for the first scenario, also in this context efficiency and security will be mainly affected.

Finally, the last scenario (Investment Opportunities) focuses on the combination between the complete digitization of the assets of a company and the new business models that this major change could generate. As already mentioned in previous paragraphs, industries are experimenting many ways to facilitate the access to capital. Since the explosion of ICOs in 2017, new and easier ways to access capital have become possible and achievable. However, due to their unregulated nature, ICOs still present numerous potential threats (Projection 14 did not reach consensus). For this reason, other solutions, such as STOs (Security Token Offerings), are on the way of being tested. Bringing a higher degree of freedom to investments will allow companies to receive funds from diverse and non-traditional investors, and it will also boost investments by private individuals into early-stage companies. Efficiency and innovation will be at the core of this last scenario.

5 Conclusions

In this paper, we studied different blockchain-based projections and we assessed their likelihood and impact thanks to the participation of a pool of experts. We built our findings around three dimensions (efficiency, security, and innovation) and we derived four scenarios based on experts’ shared vision. Being the current literature widely fragmented, we believe this research represents a useful starting for conceptualizing blockchain potential and implications. While many research papers focus on blockchain specific applications or general reviews of the state of the art, we try to propose a unifying framework building on different typologies of insights and analyses. We merged quantitative observations derived from standard statistics with qualitative insights obtained directly from experts’ opinions.

Overall, we believe our research can constitute a useful tool for many practitioners involved in the innovation ecosystem and for managers of small, medium and large enterprises to look at future possible scenarios in a more rational and systematic way. From one side, a company’s management can use these forecasts as a starting point for the implementation of new strategies. As previously highlighted, blockchain offers endless possibilities. However, the ability to focus on activities and projects with a positive return on investment will be crucial. Firstly, managers will face the choice between insourcing or outsourcing the technological development of the platform. While the former choice ensures higher flexibility, it also generates high development and maintenance costs. Companies which will identify blockchain as their core service will be entitled to adopt this first strategy, while the majority of the enterprises will probably gain better competitive advantages adopting Blockchain as a Service (BaaS) solution. This latter approach will boost companies’ performances, by enhancing new service offerings as well as a new level of operational efficiency, without carrying the burden and costs of technological complexity.

As mentioned, we believe this research provides useful insights for policy makers as well. The adoption of blockchain represents a tremendous technological change bringing along interesting and tangible opportunities. However, different threats can be foreseen. Central authorities do not only solve the problem of trust in certifying value transactions. They also provide essential supervision on the process itself, for example ensuring that information asymmetry is kept at reasonable levels between parties engaging in any sort of contracts, especially in the financial world. Letting people directly exchange value between themselves or allowing companies to easily raise capitals can boost financial efficiency, but also provides room for frauds and ambiguous behaviours. Today, companies which are interested in raising capitals both through innovative tools such as crowdfunding or through traditional entities such as public financial markets, have the duty to disclose relevant information and usually go through a deep process of due diligence. Regulators should ensure the same level of control on companies that will raise money through Initial Coin Offerings or other sort of blockchain-enabled offerings. We believe that the first step towards a fair regulation of this newly born technology is the understanding of its foreseeable impact on the society in the near future. This work aims to be a precious enabler in this direction. As highlighted in the body of this research, it appears fundamental for policy makers, regulators and government to deeply understand the potential upsides and threats of this new technology, and to correctly navigate the different possible blockchain-enabled scenarios. The successful cooperation between companies’ management and regulators could enable significant productivity shifts in the economic tissue of many countries. Failing in efficiently grasping and enhancing these new paradigms from a regulatory perspective could result into a heavy deficit for the competitive edge and productivity of the industrial sectors of the governments’ respective countries, potentially leading to macroeconomic differentials in productivity.

To conclude, this research could be a useful reference for orienting into this complex and dynamic environment, reducing the perceived uncertainty associated to such a new technology. Thanks to the experts’ advice, it is now possible to have a clearer picture of the evolution of blockchain technologies and of the opportunities and threats that the technology will generate. Certain limitations and characteristics of this study must be considered to correctly and effectively take advantage of its results. The main objective of this work was to examine the most disrupting aspects that are likely to occur in Europe by 2030, with a particular focus on how the technology will facilitate financing, reduce costs, increase transparency and, in general, influence firms’ business models. From this point of view, the objectives and assumptions presented at the beginning of this paper can be considered as fully achieved, but further works exploring other industries and geographies are required to get an organic understanding of the new enhanced paradigms.

Our research only paves the way for a better understanding of what a blockchain-based future will look like, as the differences between industries are too large to be analyzed in a single work. Organizations and businesses in the financial world are consistently changing, but it will be necessary also for companies belonging to different sectors to completely rethink their core activities. From this perspective, we believe further works are needed in these directions. We hope researchers will use and explode our framework to further characterize and meticulously describe the new possible paradigms around the multiple dimensions examined in this work.

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The landscape of Blockchain research: impacts and opportunities

• Published: 07 November 2021
• Volume 19 , pages 749–755, ( 2021 )

Cite this article

• Hsing Kenneth Cheng 1 ,
• Daning Hu 2 ,
• Thomas Puschmann 3 &
• J. Leon Zhao 4  

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Blockchain technology has emerged as an important research domain in recent years. It not only supports the secure and efficient storage and processing of information but may also transform the business principles and processes embedded in traditional centralized organizations and societies. This editorial first provides a framework that identifies the emerging areas of blockchain research. The key characteristics of this framework in Blockchain 1.0, 2.0, and 3.0 are defined and introduced. The impacts and opportunities associated with blockchain research are identified and discussed. At last, the six articles in this special issue are characterized using the proposed research framework of blockchain research.

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1 Introduction

The notion of blockchain technology and its applications in various business domains have attracted a lot of attention. Although the most well-known application of blockchain technology is Bitcoin, its applications go far beyond cryptocurrency. In this editorial, we introduce six articles included in our special issue which encompass a number of important topics on blockchain technology and applications, and discuss the current status and opportunities of research in this emerging area mainly from the business perspective.

Blockchain is based upon the novel ideas of a distributed ledger, an innovative approach of decentralized storage, and secured management of large amounts of transaction data outside the boundary of a conventional organization. Its advantages include anonymity, real-time data management, decentralization, and disintermediation. With these features, blockchain revolutionizes how transaction information is stored and managed in networked markets and institutions. Currently, the majority of blockchain applications concentrated in the information technology and financial domain. But more and more blockchain applications are expanding to other important areas like supply chain and the Internet of Things.

Information Systems (IS) scholars are becoming increasingly interested in studying blockchain technology and applications. This special issue includes six studies on this topic using various research methods like design science, behavioral research, or IS economics. As Table 1 shows, previous research (Zhao et al. 2016 ) has suggested that the development of blockchain technology has gone through three generations, namely, Blockchain 1.0 for digital currency (cryptocurrency), Blockchain 2.0 for digital finance, and Blockchain 3.0 for digital society (Xu et al. 2019 ). This editorial extends on this framework to lay a foundation for these six articles and identify several promising research directions in blockchain research from a business research perspective.

2 Blockchain 1.0

The blockchain technologies and applications in digital currency (especially cryptocurrency) is often referred to as blockchain 1.0. Cryptocurrency has attracted a lot of attention largely because of the rise of the Bitcoin over the past ten years. Bitcoin has envisioned an innovative form of digital currency—cryptocurrency. Nowadays, the majority of global blockchain companies are related to cryptocurrency. Cryptocurrency has challenged the traditional paradigm of state-controlled currencies and the dominant role of central banks, as well as the conventional financial institutions (Dong 2018 ). In recent years, many central banks are also preparing to launch their own fiat digital currencies.

Given the volatile nature of existing cryptocurrencies, they were considered as a type of risky financial asset (Guesmi et al. 2019 ). There is a stream of research studying the cryptocurrency markets from the perspectives of market efficiency, volatility clustering, and portfolio management (Corbet et al. 2019 ). The hype of Bitcoin also led to a lot of research related to Blockchain technology. We conducted a search of “blockchain” in the Web of Science search engine provided by Thomson Reuters and found 3,413 published articles (As of 06–26-2020).

The first paper in our special issue “ A Scientometric Review of Blockchain Research ” adopted multiple scientometric methods to generate a panoramic view of the recent developments in blockchain research. It identifies four research aspects in current blockchain research: underlying technology architecture, privacy and security, financial applications, and smart scene applications. Based on the results of literature detection and structural variation analysis, they suggested two important emerging trends in blockchain research: 1) solving problems caused by applying cryptocurrencies in the real world, and 2) improving blockchain technology based on specific application requirements.

The second paper “ a survey of blockchain with applications in maritime and shipping industry ” categorizes recent blockchain research (2015–2018) into four areas: hardware, software, emerging technology, and business applications. It examined the impacts of blockchain technology and applications on cost, quality, speed, and risk assessment in shipping and supply chain management. The authors found that the mechanisms of blockchain that can greatly improve the efficiencies of international shipping and supply chain. Lastly, the study evidenced the increasing transparency and accountability of international shipping provided by blockchain technology.

3 Blockchain 2.0

Blockchain 2.0 was often referred to as financial applications of blockchain besides digital currency, such as securities trading, supply chain finance, and banking instruments (Xu et al. 2019 ). For instance, blockchain has been transforming traditional trading methods in practice. Kim and Journal ( 2018 ) proposed that blockchain can reduce the time of key trading processes, including currency transactions and identity verifications, thereby improving efficiency in record keeping and equity trading. Similarly, Gomber et al. ( 2018 ) suggested that blockchain is a disruptive financial innovation for supporting new business models and market mechanisms. Moreover, previous studies have envisaged that blockchain technology can greatly transformed traditional banking operations through its advantages in speed, accuracy, reliability, security, and traceability (Arvind and Biot‐Paquerot 2018 ; Mori 2016 ). Chen et al. ( 2017 ) found that blockchain can change the way banks communicate with customers, as well as business models and even the banking ecology.

Following this line of research, the paper “ The impact of Blockchain on Business Models in Banking ” studied how blockchain affect banking business models. It developed a research model that connects IT innovations with the three banking value disciplines: operational excellence, customer intimacy, and product leadership, and the four generic elements of business models: "what", "who", "how", and "value". This model was examined through surveying 104 executives of both banks and non-banks around the world. The results show that all three value disciplines are significantly affected by blockchain technology.

Another common Blockchain 2.0 application is smart contract that can automatically execute various business processes based on pre-specified concepts and rules. It has revolutionized traditional financial transaction and payment systems. Two important extensions of long-term smart contracts are decentralized autonomous organizations (DAOs) and Decentralized Autonomous Corporations (DACs), which contain the digital assets and encode the bylaws of an entire organization and corporations. These concepts are the foundation of the development and user communities under the emerging Fintech platforms. Moreover, smart contracts are traceable and irreversible. They allow transaction records to be maintained publicly in a secure and trustful environment (Wang et al. 2019 ). Current application domains of smart contracts include Decentralized finance (DeFi), supply chain management, Internet of Things, healthcare, insurance, and financial systems (Mohanta, Panda, and Jena 2018 ).

The paper “ Laying the Foundation for Smart Contract Development: An Integrated Engineering Process Model ” proposes an integrated process model for engineering Distributed Ledger Technology (DLT)-based smart contracts. This model can be iteratively refined by domain experts. It explicitly accounts for the immutability of the trustless, append-only, and decentralized DLT ecosystem, thereby overcoming certain limitations of traditional software engineering process models. The model consists of five phases: conceptualization, implementation, approval, execution, and finalization. Applying such a model of engineering smart contracts can help developers better understand and streamline the engineering process of DLTs. This model can also serve as a generic framework of supporting DLT-based application development in general.

4 Blockchain 3.0

The blockchain technology envisioned a new form of the economy with the core value of trust. Blockchain 3.0 is a blueprint for popularizing the technology in fields other than cryptocurrency and finance, such as government, health, science, culture, and the arts (Swan 2015 ). It focuses on the regulation and governance of blockchain-based decentralization in every aspect of society.

A main challenge that blockchain technology aims to tackle is to promote trust through reliable and efficient information sharing, given its characteristics such as distributed operation, authentication, the immutability of records, and cryptography. Luhmann ( 2018 ) categorized trust into two types: personal and system trust. Personal or organizational relationships and emotional bond promote the former type of trust, while consensus rules enforce the latter. The adoption of blockchain technology allows us to replace personal trust with system trust. Therefore, blockchain technology as a “truth machine” has the potential to reshape the business relationships and processes in society.

In this special issue, the paper entitled “ How can we reduce information asymmetries and enhance trust in the market for lemons? ” explores how blockchain can reduce information asymmetry in a used car market. They demonstrated that the blockchain-based platform helps reduce information asymmetries. Trust in the IT artifact plays a vital role as a mediator in building initial trust in the system itself. By employing the design science approach, they demonstrated how the provision of car usage data in a blockchain platform can reduce information asymmetries and enhance trust in the used car market.

Moreover, blockchain technology has many applications in supply chain management. Tracking goods through the production and delivery process requires automated compliance to freight and trade regulations. Schmidt and Wagner ( 2019 ) argued that blockchain technology limits opportunistic behavior, environmental, and behavioral uncertainty. Correspondingly, it could reduce transaction costs and enables more market-oriented governance structures.

The paper " Processes, Benefits, and Challenges for Adoption of Blockchain Technologies in Food Supply Chains: A Thematic Analysis " examined the processes, benefits, and challenges of adopting blockchain technologies in food supply chains. This paper adopted the thematic analysis method to identify seven first-order themes and two second-order themes in adoption processes; thirteen first-order themes, sixteen second-order themes, and five third-order themes in benefits; and fourteen first-order themes and five second-order themes in challenges. Its findings help us to better understand the benefits and challenges of adopting blockchain in food supply chains.

5 Future research directions

Beyond the three-type categorization of blockchain development, an emerging field that is based on blockchain technology is Decentralization Finance, often referred to as ‘DeFi’. It is a novel experimental form of finance that does not rely on central authorities or intermediaries like exchanges or banks but mainly utilizes smart contracts. Technically, DeFi does not refer to a single project but an overall integration of decentralized financial services and applications that are based on blockchain technology (Abdulhakeem and Hu 2021 ). For example, Facebook’s stable coin Diem aims at offering a global digital payment method independent from financial institutions. DeFi aims to provide a low-cost, fast, efficient, trustworthy, and completely transparent global financial ecosystem that operates over the internet without any central authority and is highly accessible to everyone around the globe (Abdulhakeem and Hu 2021 ).

As the DeFi field is still very young compared to the aforementioned blockchain research topics, it has many possible research directions with great potential, such as stable coins, liquidity pools, decentralized exchanges, decentralized governance mechanisms, as well as unique security issues. We believe that DeFi research will attract a lot of interests in the near future.

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Cheng, H.K., Hu, D., Puschmann, T. et al. The landscape of Blockchain research: impacts and opportunities. Inf Syst E-Bus Manage 19 , 749–755 (2021). https://doi.org/10.1007/s10257-021-00544-1

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Introduction to blockchain.

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Decentralization of Blockchain

Blockchain is decentralized, meaning it’s not controlled by a single entity. Instead, everyone in the network has access to the entire blockchain. No one can claim ownership or control over the information, making it fair and democratic.

Uses of Blockchain

Blockchain isn’t just for Bitcoin. It’s also used in supply chain management, healthcare, and voting systems. It helps to track goods, secure patient data, and ensure votes are counted correctly. It’s a versatile technology with many potential uses.

Future of Blockchain

The future of blockchain is bright. As more people understand its benefits, its use will likely grow. It could help solve many problems, from financial fraud to voter fraud, making our world more secure and fair.

250 Words Essay on Blockchain Technology

What is blockchain technology.

Blockchain technology is a type of computer technology that keeps records of all transactions in a secure way. It’s like a digital ledger. Imagine a book where you write down everything you spend money on; blockchain works in a similar way. But instead of one person keeping the book, it’s shared with many people.

How Does It Work?

Each transaction made is put into a ‘block’. Once the block is filled with transactions, it’s added to a ‘chain’ of other blocks. That’s why it’s called ‘blockchain’. Everyone who is part of this system has a copy of this chain. This makes it hard for anyone to cheat or change the information because everyone else can see it.

Why is it Important?

Blockchain technology is important because it’s very secure. It’s hard for hackers to change the information in the blocks. This makes it a good system for things like money transfers. It’s also transparent, meaning everyone can see the transactions. This can help stop fraud.

Apart from money transfers, blockchain technology can be used in many other areas. For example, it can be used in voting systems to make sure votes are not changed or in supply chains to track products from where they are made to where they are sold.

In conclusion, blockchain technology is a secure and transparent way of keeping records. It has many uses and could change the way we do many things in the future.

500 Words Essay on Blockchain Technology

Understanding blockchain technology.

Blockchain technology is a kind of digital ledger. A ledger is like a book where you keep a record of transactions. For example, if you have a piggy bank, you might keep a ledger to record every time you put money in or take money out. But instead of being a physical book, a blockchain ledger is stored on computers all over the world.

How Does Blockchain Work?

Imagine a chain of blocks, where each block is a record of transactions. When a new transaction happens, it is added to a new block. This block is then attached to the chain. The special thing about blockchain is that once a block is added to the chain, the information inside it cannot be changed or removed.

Each block contains a special code called a ‘hash’. This hash is like a fingerprint, it’s unique for each block. It also contains the hash of the previous block in the chain. This makes it super tough for anyone to tamper with the blocks, because if they change one block, they would have to change all the blocks that come after it too!

Why is Blockchain Important?

Blockchain technology is important because it is very secure. Since it is stored on many computers, it is difficult for hackers to change the information. This makes it a good system for things like money transactions, where security is very important.

One popular use of blockchain technology is for a type of digital money called ‘cryptocurrency’. The most famous cryptocurrency is Bitcoin. When people send or receive Bitcoin, the transaction is recorded in a blockchain. This makes it difficult for anyone to steal or fake Bitcoin.

Blockchain technology is not just for money transactions. It can be used for many other things too. For example, it can be used to keep track of goods as they are moved from one place to another. This can help to prevent theft and fraud.

It can also be used to store information securely. For example, it could be used to store medical records. Because the information in a blockchain cannot be changed, it could help to prevent false information from being added to a person’s medical record.

In conclusion, blockchain technology is a new and exciting way to store and secure information. It is like a digital ledger that is stored on many computers around the world. It is very secure and can be used for many different things, from money transactions to tracking goods to storing medical records. As we move more and more into the digital age, it is likely that we will see more uses for this amazing technology.

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Essay on Blockchain Technology

Introduction.

A blockchain is a series of time-stamped immutable data usually managed by a group of computers in most cases not owned by single entities. The individual blocks of data are bound and secured using cryptographic principles. Thus, a blockchain has no central authority and operates more like a democratized system. The blockchain system is an immutable ledger; therefore, the information is open for every individual on the platform to view. Every individual is therefore accountable for their actions within the blockchain network. There are no transaction costs involved in blockchain transactions apart from the infrastructure cost. Blockchain is the simplest way of passing away from two points though ingenious. First, the deal is safe and fully automated. Once a transaction is initiated, a block gets created (Crosby, Pattanayak, Verma, & Kalyanaraman, 2016). Then, the block gets verified by other networks of computers, probably in millions or thousands. Once the block gets verified, it’s added into a chain, usually stored across the web. Thus, a single record with a unique history gets created. The world of business is currently diversifying, and every company is trying to cut on expenses that increase the operation cost overall. Blockchain ensures that individuals get paid for the services and goods they offer without hidden charges. Blockchain cuts the fee-processing middleman and eliminates the necessity for a match-making platform. The transaction in the blockchain is free as businesses can charge in minuscule amounts for their services. Taking, for instance, a video streaming platform can charge 1/100 of a cent if a customer or user wants to view a section of the videos. Traditional businesses rely on monthly or annual subscriptions to provide their services. For instance, a person who would only be interested in a section of Forbes Magazine will not pay for the entire magazine. Bitcoin uses such a model for monetary transactions, but the method can find usage in many other ways. For instance, a public transport payment system like train or tram buses. Travelers will buy tickets through the web or a mobile application and pay through credit card. The credit card companies will take cuts to affect the transaction. However, with blockchain, the bus company will save on costs when the credit company processes the deal. The entire ticketing will, therefore, get moved to the blockchain. In such cases, the parties in the transaction are the transport company and the passenger. The ticket in the scenario is the block that gets added to the ticket blockchain. Transactions on the blockchain are unique and get verified independently. The tickets will also get checked separately. The last ticket on the blockchain also indicates a record for all transactions done. The entire blockchain process, therefore, will replace any processor models that charge for a purchase committed. Businesses like recorded music sales are bound to profit as the artists would no longer rely on the various music companies and distribution platforms like Amazon, Apple, and Spotify. The musicians will get the full benefit from their works. For music cases, the downloaded music can be encoded within the chain and archived the music purchased in a cloud in blockchain technology. The amounts charged are minimal; hence there will be no need to subscribe to the various streaming websites and platforms (Daniel, 2017). Other services like eBooks are likely to fit in the blockchain system perfectly. Amazon is cutting with the current systems, and the credit companies are equally earning from the sales. With blockchain, books would get circulated in an encoded form. All successful transactions will eventually get channeled to the author and not royalties. The financial world may be the biggest beneficiary of blockchain technology. The technology is set to revolutionize how stock exchange gets managed, insurance contracts, and loans bundled. Blockchain is set to eliminate bank account and other services primarily offered by the banking sector (Daniel, 2017). Elimination of such transactions may render most banks bankrupt, forcing most institutions to change their system of operations. The banking institutions may be turned into financial advisers while the stockbrokers are unlikely to earn any commission as the buy and sell spread in the stock market will disappear.

Previous approaches

The conventional methods of payment have for many years denied businesses the potential of getting maximum profits. The banks and credit card companies charge a massive sum of money to effect transactions within different platforms. Blockchain may be a new technology though it has received praise and backlash in the mainstream sector. The technology of blockchain is believed to be the most significant innovation in finance. In the Renaissance period, merchants had a problem with their bookkeeping; therefore, double-entry bookkeeping emerged. The double-entry was so helpful that it led to the formation of corporations by different investors and entrepreneurs, thereby giving rise to modern-day capitalism. The double-entry ledgers still needed verification from a third party who could be trusted to ascertain that the information was correct. Others believe blockchain technology is similar to the 1970s TCP/IP, a networking protocol that allowed the computer to communicate and swap data. A protocol that formed the backbone for the invention of the internet. Five hundred years after the Renaissance, blockchain added a new entry of ledger which verifiable cryptographically and is much safer and transparent to the standards set by the global financial systems.

Current approaches

Major financial institutions are currently researching to create a proof of concept and further hunt for talent in blockchain technology. The number of individuals learning or interested in acquiring skills in blockchain has trebled, and the number is set to increase in the coming days. The wave of blockchain is taking over the finance sector and other industries like energy, health, and food technology, which are seen initiating pilot projects and joining groups trying to figure out how blockchain operates. SWIFT, a multinational organization that processes international payments, recently embarked on a pilot project in which the results are to be validated by some twenty-two banks. TUI Group, which is known as a world leader in tourism, currently uses blockchain to track the contracts issued internally. Airbus is also projecting to use blockchain to monitor the complex parts involved in making a jet plane. Blockchain technology gets more useful when monitoring the movement of goods since all transactions need to go through the ledger. The system keeps a copy of the transactions, therefore, providing instant access when required. A good example would be Maersk, the shipping company that has started a test for monitoring shipment and coordinate with the customs officials in the different countries of operation. State agencies are also getting a form like the Colombia central bank, which joined one of the consortia operating globally. The Russian government also announced plans to commence building a quantum computing and blockchain research hub to enable members of its citizen to acquire knowledge in the new form of technology slowly taking over markets. In collaboration with the Bank of Japan, European Central Bank has launched a blockchain research project (Ølnes, Ubacht, & Janssen, 2017). Blockchain gets praised, and most analysts believe the technology has the potential of disrupting several industries just like the internet did two decades ago. However, few distributed applications are in the mass market, and some large companies continuously shy away from the technology. Moreover, some companies that initiate pilot projects do not move to the next step after showcasing (Nam, Dutt, Chathoth, & Khan, 2019). Perhaps the leading companies in technology have not pushed the technology into the mainstream and popularized it.

Cryptocurrency and Blockchain Technology

Cryptocurrencies are by far the most popular form of blockchain technology and in the recent days there have been various debates as cryptocurrency’s popularity gets higher. Digital currencies such as Bitcoin, Ethereum, and Litecoin have become popular and even major businesses are beginning to accept cryptocurrency as payment. Close to 6,700 cryptocurrencies are available globally resulting to a market cap of almost $1.6 billion with Bitcoin enjoying the bigger share (Kasar, 2021). The security details of blockchain makes cryptocurrencies secure as each has its irrefutable unique identifier attached to a single owner. Cryptocurrencies are getting accepted more in business world with a striking example being Tesla, the electric vehicle, announcing to be accepting Bitcoin as form of payment.

The Pillars of Blockchain Technology

Blockchain technology is considered to operate based on three principles.

Decentralization

Before the invention of BitTorrent and Bitcoin, most services seemed to get centralized. Data would get stored in one platform or entity, and to get the desired information, one must interact with the data owner to receive feedback. A good example would be the banking system. The banks store our money, and the only way one can effect payment to a different party is to go through the bank. Thus, the traditional server model describes the centralized system.

When a person with a laptop or smartphone wants to navigate the web, they will send a query to the server, who will get back with the relevant information. The centralized systems for many years have served the digital platform appropriately though several shortcomings experienced. First, the data in a centralized system are in one spot, making such data vulnerable to successful hacking. Secondly, in the event of the software upgrade, the whole system would be stopped, which may lead to losses in business. System shutdowns would mean nobody can access the information they have like when Gmail or Yahoo serves to get shut; individuals will not have access to their emails. Finally, a decentralized system gives the users the freedom to interact with their peers without necessarily going through a third party. For instance, the principle behind Bitcoin is that the developers needed a way where individuals have full control of their money. One may send them to anyone they desire without communicating with the bank.

Transparency

The concept of transparency in the blockchain is often misunderstood. Some analysts would say the technology provides privacy, as some say it is transparent. In the blockchain, a person’s identity gets hidden through complex cryptography and is only presented using the public address (Pilkington, 2016). For example, checking on a person’s transaction history would not give “Joe sent 10 BTC”; instead, one will see “1MG1thsFLkBzzz9vpFY3mvqqT2TbyCt7Bzj sent 10 BTC.” Thus, the person’s identity would be secure though all the transactions would still be visible through their public address. Such a level of financial transparency has not been witnessed with any technology before. Every individual, therefore, is accountable for the transactions they make, making it easier for financial institutions to monitor suspicious dealings.

In cryptocurrency, for instance, once an individual knows the public address of the companies or persons, all that is required is to load it on an explorer, and all the transactions they have engaged in will show (Crosby, Pattanayak, Verma, & Kalyanaraman, 2016). The system will force corporations and companies to be honest in their dealings. Though companies may not fully transact using cryptocurrencies, they may need to hide some books, perhaps to evade taxation. Further integration of the supply chain in blockchain technology would force most, if not all to transact faithfully.

Immutability

The pillar of immutability in blockchain implies that if something gets into the blockchain, tampering would be difficult, and that would be valuable for financial institutions. Embezzlement cases will reduce significantly, and individuals will not fiddle with a company’s accounts. Blockchain operates using a cryptographic hash function. Hashing means having an input string of any desired length though the output will be of a fixed period (Giungato, Tarabella, & Tricase, 2017).

In the above example, one would notice that the resultant output will have a fixed number of bits’ length, whether big or small input. The concept of hash becomes useful while dealing with extensive data and transactions. Remembering the input may sometimes get unnecessary due to its length, so the hash can help keep track of the sale.

Maintaining Blockchain Network and Nodes

The blockchain gets maintained by the peer-to-peer network, a collection of nodes interconnected to each other (Pilkington, 2016). The nodes are single computers taking in different inputs to perform a particular function and later output. Blockchain partitions the whole workload among the participants, and their no central server as several decentralized peers.

The peer-to-peer network is appropriate for file sharing. The client-server model at times gets slow and depends on the stability of the server. You may still have more peers to download from with a decentralized network, even if one peer goes out of the network (Pilkington, 2016). The system in peer to peer is not prone to censorship hence preferred by most individuals.

The technology of blockchain is set to revolutionize how transactions are going to get conducted in the future. Currently, there are high demands for blockchain developers. The technology cuts out brokerage and intermediaries in operations and further reduces the possibility of fraud and embezzlement in state agencies and business organizations. Transactions done online are in most instances connected to identity verification, making transactions tamperproof. The technology of blockchain will give internet users the possibility of creating value by authenticating their digital information. The different arguments against blockchain-based technologies are warranted, however, the popularity and acceptability of the technology is likely to push governments and other stakeholders into accepting it as a legitimate form of payment and probably legislate and have regulations in place.

Crosby, M., Pattanayak, P., Verma, S., & Kalyanaraman, V. (2016). Blockchain technology: Beyond bitcoin. Applied Innovation, 2(6-10), 71. Daniel, R. (2017). Understanding Blockchain: Explore the Full-Circle Effect Blockchain Technology Has on the World and Our Future Generations (Books on Bitcoin, Cryptocurrency, Internet Money, Invest Ethereum, FinTech). Createspace Independent Publishing Platform. Giungato, P., Rana, R., Tarabella, A., & Tricase, C. (2017). Current trends in the sustainability of bitcoins and related blockchain technology. Sustainability, 9(12), 2214. Kasar, N. D. (2021). Review on Cryptocurrency and Blockchain Management (No. 5312). EasyChair. Nam, K., Dutt, C. S., Chathoth, P., & Khan, M. S. (2019). Blockchain technology for smart city and smart tourism: latest trends and challenges. Asia Pacific Journal of Tourism Research, 1-15. Ølnes, S., Ubacht, J., & Janssen, M. (2017). Blockchain in government: Benefits and implications of distributed ledger technology for information sharing. Pilkington, M. (2016). 11 Blockchain technology: principles and applications. Research handbook on digital transformations, 225.

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Blockchain and Bitcoin Technology Term Paper

The invention of the Internet has led to new technologies that are revolutionizing information sharing, use, handling, and application. Blockchain is a modern innovation characterized by time-stamped data records managed by numerous computers without a single owner. Technologists apply cryptographic chains or principles to secure such data blocks and remain bonded to one another. Such a series of data records are distributed in a free manner without a central source of authority. The literature review presented below describes the possible future trends of blockchain and bitcoin technology, future trends of its application, and the potential implementation in the United Arab Emirates (UAE) private and government sectors.

Literature Review

Background information.

The origin and invention of blockchain technology are attributable to an unknown person called Satoshi Nakamoto. Some analysts and technologists believe that the identity of the expert could be a group of programmers (Weldon & Epstein, 2019). However, the concept of cryptography emerged in 1991 after Scott Stornetta and Stuart Haber conceived an ingenious idea of creating secure timestamps for documents. The adoption of Merkle trees made their original design more efficient and capable of condensing certificates into a single chain or block. Nakamoto went further to improve the model by adopting the Hash-cash model to timestamp data blocks without the need for trustees to sign them.

A powerful or difficult parameter was introduced that resulted in the stabilization of the established information sets. This framework would eventually become the basis or foundation of the bitcoin cryptocurrency. This is a public ledger for the major financial transactions executed on

the global network (Andoni et al., 2019). Weldon and Epstein (2019) indicate that bitcoin blockchain had already grown exponentially to around 20 GB by 2014. Due to the expanding nature of this ledger, experts argue that it will have exceeded 200 GB by 2021 (Weldon & Epstein, 2019). The efficiency and nature of this invention has encouraged organizations to consider new ways of experimenting with blockchain technology.

Future Trends of the Applications of Blockchain and Bitcoin Technology

The principles of this technology explain why its applicability in different fields and areas is unavoidable. Depending on the nature of the developed blockchain, stakeholders, users, or parties are in a position to view previous entries while at the same time entering new ones. The existence of complex guidelines explains why anyone would not just add new data or records. A powerful cryptocurrency model is, therefore, in place to prevent the available digital content from being destroyed or forged. Consequently, Leible et al. (2019) believe that future users will find it trustable and capable of supporting trusted transactions. The fact that no central authority is needed explain why their decentralized model remains useful. The integrated and stable nature of blockchain explains why it has continued to support digital currencies. Schackelford and Myers (2017) go further to indicate that such a technology is capable of impacting a wide range of transactions and service provision practices. While this invention is still in its infancy, chances are high that it will find numerous uses in various fields.

The UAE government and businesses rely on transactions and processing systems to provide timely support to the targeted clients. Unfortunately, the current rate at which value is transferred from point A to B remains slow, uncoordinated, and sometimes expensive (Leible et al., 2019). Transactions taking place between the United Arab Emirates (UAE) government and international businesses tend to take time before processing, execution, or transmission. This challenge affects stakeholders due to the fact that there are numerous stakeholders and protocols that need to be taken into consideration. Blockchain invention is a new model that can make such cross-border transactions and payments more efficient (Ismail et al., 2019). This technology will minimize the incurred costs and deliver real-time processing and transactions. This approach will make it possible for many companies and governments to achieve their goals.

The nature and efficiency of blockchain and bitcoin innovations make them the best targets for supporting smart contracts. This framework means that all agreements and their details will be supported using computer programs. The fulfillment of all requirements and the completion of the payment procedures will result in self-enforcing or executing contracts (Jun, 2018). This approach will improve the level of transparency and security. The costs of formalizing agreements will decline and make it possible for more companies and governments to achieve their goals. Those involved should be aware of the potential drawbacks of such smart contracts and consider new ways of improving their effectiveness in the world of business.

The emergence and continuous use of the Internet in Dubai presents a number of challenges that might affect individuals, the UAE government, and even corporations. One of these predicaments that many stakeholders stand to encounter is that of identity theft. With the increasing number of hacking and phishing cases, it becomes possible for companies to embrace the power of blockchain to transform the manner in which users can identify their partners and clients (Zhang et al., 2019). The independent approach for verification and the inability to duplicate blockchains means that all verification processes are simplified and transparent. The government can go further to embrace blockchain model to support voter registration and ballot casting systems (Beck et al., 2017). Such a system will ensure that the collected data is secure and transferred across all the intended platforms and systems. Additionally, the information will be accessible to more people while at the same time remaining secure.

The business world has a potential to embrace the utilization of blockchain and bitcoin technology to transform supply chain processes. Makridakis and Christodoulou (2019) assert that the globalizing global community has created a scenario whereby many suppliers, customers, and marketers in UAE and across the world remain interlinked. However, such systems are usually time-consuming since transactions will need to be verified and match the demands and expectations of all the involved partners. This model has been found to result in delays, wastes, and sometimes mismatches (Andoni et al., 2019). Blockchain technology remains promising in this area of logistics since it will promote efficiency, authentication, and processing of information. The strategy has the potential to reduce human effort by 100 percent and locate errors that could affect the process negatively (Zīle & Strazdiņa, 2018). The lessons gained from the current application and proliferation of bitcoin cryptocurrency means that there are several untapped areas of blockchain technology. Those involved will need to focus on the potential benefits and consider new ways of meeting the demands of all key stakeholders.

Arguments and Counterarguments

The above possible applications of blockchain and bitcoin technology mean that it presents numerous opportunities to government agencies and companies. First, companies can embrace the power of this innovation to develop data sets that will streamline operations and ensure that customers’ demands are identified and fulfilled. For example, the technology can reduce different forms of data duplication and identity theft (Kogure et al., 2017). Users can pay for services and products instantly without room for error. Second, blockchain is a game changer for companies that want to overcome the challenges experienced when acquiring raw materials overseas or exporting different finished products. The framework has the potential to streamline operations and focus on the expectations of individual partners.

Third, these technologies create a sense of security since the acquired and stored information blocks are verified and protected against unauthorized users while at the same time being available to all partners. Companies can compete successfully with established corporations by adding value to their customers, streamlining business operations, and maximizing profits (Yli-Huumo et al., 2016). Fourth, governments can rely on blockchain technology to streamline a wide range of operations intended to provide timely, efficient, and personalized services to all citizens (Ruoti et al., 2019). This model will minimize cases of duplication or errors. Different departments can link their data sets to ensure that the targeted citizens receive transparent and timely support or services. The increased level of coordination from the use of blockchain technology can empower more citizens to pursue their economic goals.

On the other hand, there are specific disadvantages that stakeholders need to consider before implementing or adopting such technologies. The first one is that they utilize large quantities of energy that might be unavailable in the developing world. Consequently, an unequal platform might emerge and make many companies and governments in the developed world more successful. The second possible drawback is that this form of technology is threatened by data mining (Schackelford & Myers, 2017). While the blockchain tend to be secure and hard to hack, some ingenious ways of accessing and changing the information will emerge in the future (Liu et al., 2019). This means that many companies and individuals will be at risk of losing crucial data or financial resources. The third possible disadvantage associated with the future applications of this technology is that blockchain sets are usually not permanent. Some programmers can alter them and undermine their efficiency.

This weakness explains why they might fail to resonate with the long-term expectations or goals of different corporations. Finally, blockchain technology still remains limited in terms of accessibility and supportive resources. Those relying on it will be unable to meet the demands of all citizens or customers in every corner of the targeted country (Woodside et al., 2017). These unique attributes explain why it would be necessary for different stakeholders to focus on the potential challenges and opportunities associated with blockchain technology and make appropriate decisions.

Conclusions

The above literature review has identified blockchain as a superior technology that has a wide range of applications. The government and established businesses in the UAE can rely on it to achieve numerous gains, provide high-quality services and support to citizens or patients, and minimize cases of identity theft. It presents additional opportunities for safeguarding information, streamlining transaction processes, and improving supply chain procedures. However, this invention has specific challenges that explain why it should not become an automatic game changer for governments and business organizations. In conclusion, all stakeholders should consider the outlined benefits and match them with the potential barriers that might affect their implementation and make informed decisions.

• Andoni, M., Robu, V., Flynn, D., Abram, S., Geach, D., Jenkins, D., McCallum, P., & Peacock, A. (2019). Blockchain technology in the energy sector: A systematic review of challenges and opportunities. Renewable and Sustainable Energy Reviews, 100, 143-174.
• Beck, R., Avital, M., Rossi, M., & Thatcher, J. B. (2017). Blockchain technology in business and information systems research . Business & Information Systems Engineering, 59, 381-384. Web.
• Ismail, L., Hameed, H., AlShamsi, M., AlHammadi, M., & AlDhanhani, N. (2019). Towards a blockchain deployment at UAE university: Performance evaluation and blockchain taxonomy. Association of Computing Machinery, 1, 30-38. Web.
• Jun, M. (2018). Blockchain government – A next form of infrastructure for the twenty-first century . Journal of Open Innovation: Technology, Market, and Complexity, 4, 7-18. Web.
• Kogure, J., Kamakura, K., Shima, T., & Kubo, T. (2017). Blockchain technology for next generation ICT . FUJITSU Science and Technology Journal, 53 (5), 56-61. Web.
• Leible, S., Schlager, S., Schubotz, M., & Gipp, B. (2019). A review on blockchain technology and blockchain projects fostering open science . Frontiers in Blockchain. Web .
• Liu, M., Wu, K., & Xu, J. L. (2019). How will blockchain technology impact auditing and accounting: Permissionless versus permissioned blockchain . Current Issues in Auditing, 13 (2), A19-A29. Web.
• Makridakis, S., & Christodoulou, K. (2019). Blockchain: current challenges and future prospects/applications . Future Internet, 11 (11) , 258-273. Web.
• Ruoti, S., Kaiser, B., Yerukhimovich, A., Clark, J., & Cunningham, R. (2019). Blockchain technology: What is it good for? Communications of the ACM, 63 (1). Web.
• Schackelford, S. J., & Myers, S. (2017). Block-by-block: Leveraging the power of blockchain technology to build trust and promote cyber peace. The Yale Journal of Law & Technology, 19, 334-385.
• Weldon, M. N., & Epstein, R. (2019). Beyond bitcoin: Leveraging blockchain to benefit business and society. Transactions: The Tennessee Journal of Business Law. Web.
• Woodside, J. M., Augustine, F. K., & Giberson, W. (2017). Blockchain technology adoption status and strategies. Journal of International Technology and Information Management, 26 (2), 65-93.
• Yli-Huumo, J., Ko, D., Choi, S., Park, S., & Smolander, L. (2016). Where is current research on blockchain technology?—A systematic review. PLoS ONE , 11 (10), e0163477.
• Zhang, R., Xue, R., & Liu, L. (2019). Security and privacy on blockchain . ACM Computing Surveys, 1 (1), 1-35. Web.
• Zīle, K., & Strazdiņa, R. (2018). Blockchain use cases and their feasibility . Applied Computer Systems, 23 (1), 12-20. Web.
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Blockchain Technology in Finance

I decided to choose the topic of Blockchain Technology in Finance because I am currently pursuing a degree in Finance. As you can see why this would spark my interest. I’m intrigued about the role blockchain might have in the financial market. How it might help and advance the industry or the possibilities of the negative effects it might have amongst the financial market. I am a little confused myself as to what exactly a blockchain even is. Blockchain technology along with all these talks about NFT’s though has me believing that it is here to stay. Let’s dive a little into blockchain technology and its role in Finance to expand our understanding of the subject matter.

First, we must determine what a blockchain is. A blockchain essentially handles blocks that are uniquely identified, linked transactions that align in a chain. It’s continuously growing, distributed, ledger of these blocks which are sealed with a digital fingerprint (Treleaven et al., 2017).  A simple way of explaining this is as follows, “The defining characteristic of many blockchain platforms is the confirmation process by which new records are added to the ledger” (Treleaven et al., 2017, p. 15).   So essentially what I have gathered through this article to try and put it all in layman’s terms is that blockchain is a ledger that everybody in the network owns a copy of to help maintain the integrity of the chain. With that being said there is two key components within blockchain; distributed-ledger technology and smart contracts. “A distributed ledger is a decentralized, shared, replicated, and synchronized record of transactions between contracting parties secured by cryptographic sealing” (Treleaven et al., 2017 p.15).  Which essentially means that there is no need for a central authority to regulate the transactions. “A smart contract constitutes the rules that participants have collectively agreed upon to govern the evolution of facts in the distributed ledger” (Treleaven et al., 2017 p.15). Smart contracts summed up is a computer protocol that are automatically executed when the proper conditions have been met. Now that we have a better understanding of blockchain lets jump into its role in the financial industry.

Blockchain systems have many attributes that can be beneficial for the banking and financial markets (Treleaven et al., 2017).  The highlight of these systems that draw so much attention is the ability for them to operate as decentralized networks.  Due to this ability, it helps concrete the integrity of the systems that will in turn boost the confidence for investors. The ability to remove third parties to execute transactions removes the possibility of error occurring. So, as you can see, this could be greatly beneficial to the industry. I also believe that this could be incorporated into government practices which could in turn also instill more integrity into the system itself and generate more confidence in the public.  Blockchain seems to be the most efficient way to navigate through the millions of transactions that happen daily by replacing humans with machines.

All in all, blockchain technology has broken onto the scene and taken industries by storm. Crypto was the big catalyst for this as far as getting blockchain on the map with consumers. Although crypto and blockchain have its place in the finance industry there are many more out there to be explored. “Although cryptocurrencies brought blockchain technology to broad attention, blockchain has a vast number of other possible uses. For example, smart contracts become the management framework for private records; public records including land titles, vehicle registrations, passports and building permits” (Treleaven et al., 2017 p. 17). As you can see this technology could soon affect everyone in some way. We might all be dealing with blockchain in some form in the near future.

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