A blockchain is a distributed public ledger ⁶ that records the origin of a digital asset or transaction in a peer-to-peer network ⁷ . This data is stored on connected blocks which, when viewed in its entirety, reveals the full history and provenance of all the data on the chain. By inherent design, the data on a blockchain cannot be modified, it guarantees the fidelity and security of a record and generates trust without the need for an intermediary. A blockchain can be described as a “collaboratively managed database of shared, synchronized, and replicated records that typically does not rely on central governance” (Janowicz et al., 2018). Notably, the terms blockchain and distributed ledger technology ⁸ (DLT) are often used interchangeably, however they are not the same. DLT is wider-ranging, referring to decentralised databases managed by multiple participants. Blockchain is one form of DLT, using cryptography ⁹ and consensus protocols ¹⁰ to link blocks of data. There is no one version of blockchain, it is a class of technology with various platforms, ecosystems and protocols.

Blockchain is best known for its role in cryptocurrencies, such as Bitcoin (Nakamoto, 2008) but is increasingly being used in more traditional industries and business areas. In science, it promises to make data more reliable, untamperable, open and decentralised. It has the potential to enhance trust, facilitate peer-to-peer interactions and it needs no central authority (Extance, 2017; Van Rossum, 2017; Leible et al., 2019; Ducrée et al., 2022). For research funders, it has promise in managing health data (Swan, 2015), centralising research outputs and reducing administrative burden, particularly through the use of automated smart contracts ¹¹ (Engelhardt, 2017). These characteristics appeal to modern science, a system with no single governing body but consisting of international collaboration bound by an implicit trust in the work of others (Kosmarski, 2020). Changing norms and requirements in the scientific field, including funders emphasising open-science practices and FAIR (Findable, Accessible, Interoperable, Reusable) principles for scientific data management can all be facilitated with blockchain technology (Van Rossum, 2017).

Tokens, programmable digital assets stored on the blockchain (Voshmgir, 2020), can be used to modernise legacy systems (e.g., static databases, file share systems, single indices, etc.) with Web 3.0 ¹² features of decentralisation and incentives. Token bounties could be awarded for contributions such as sharing data; identifying unreproducible data; volunteering for academic and scientific service; actively engaging in translation, dissemination, and implementation of science; and carrying out equality, diversity and inclusion (EDI) activities. These tokens could then be staked as collateral to support research priorities, grant proposals and evaluations (Ducrée, 2020). Non-fungible tokens ¹³ (NFTs) could also be used to track research data in much greater detail. NFTs provide an indelible, time-stamped record demonstrating proof of knowledge, allowing ownership of the idea, contribution, or finding to be more firmly claimed (Ducrée, 2020; Ducrée et al., 2022).

Publishing is another area fraught with issues concerning recognition, reproducibility, access, plagiarism, publication bias and metric manipulation (Swan, 2015; Janowicz et al., 2018; Mackey et al., 2019a; Kosmarski, 2020). Blockchain could address some of these challenges potentially leading to improved and more transparent study design, greater trust in research, more collaboration and open access (Leible et al., 2019). Notably, some scholars suggest that blockchain could help improve the quality and responsiveness of a failing peer review system (Smith, 2006; Gropp et al., 2017) by awarding tokens for completing quality reviews. This is a strong use case given that peer review is the underpinning of virtually all scientific review processes, from publishing in scientific journals to funding decisions and even promotion, yet arguably lacks the appropriate incentives and measures to record and verify participation and recognition (Swan, 2015; Warne, 2016; Spearpoint, 2017; Tennant et al., 2017; Avital, 2018; Jan et al., 2018; Kosmarski, 2020).

Both industry and governments are already using blockchain with many examples listed in the work of Kosmarski (2020) and Ducrée et al. (2022). For example, the ARTiFACTS ¹⁴ platform helps establish the origin of scholarly artefacts while the Bloxberg ¹⁵ consortium provides scientists with decentralised services worldwide. Pluto ¹⁶ offers a decentralised, token-backed system where scientific data can be submitted, reputation tracked, peer review rewarded and work published. Ovarium ¹⁷ differs, aiming to integrate into the existing publication lifecycle, offering tokens, open peer review and immediate provenance tracking. Several other projects are also looking at funding, NFT economies and decentralised organisations ¹⁸ .

Closer to our work at the National Institute for Health and Care Research (NIHR), is the National Research Council of Canada. Their Industrial Research Assistance Program, an innovation funder, ran a pilot in 2018–19 where they “used the Ethereum blockchain to proactively publish grants and contribution data in real-time.” Through this experiment, they demonstrated the possible use of blockchain by government funders to support proactive disclosure ¹⁹ .

The NIHR commissions over £1.2 billion worth of health and social care research each year (National Institute of Health and Care Research, 2021). Proposals are selected through a competitive commissioning process, usually involving two stages. Stage 1 applications are reviewed, discussed and scored by a committee of academics and members of the public. Shortlisted applicants are then invited to submit a full Stage 2 application which undergoes peer review by both expert and public reviewers. These reviews inform the assessment, discussion and scoring by the Stage 2 committee. If successful at Stage 2, proposals are recommended for funding to the Department of Health and Social Care, who then ratify the decision to fund. Once a research project is underway, award holders are required to submit regular progress reports and a final report. Throughout this commissioning and management process the NIHR often requires specialist academic advice for work such as priority setting, project advisory groups and strategic planning.

Formal recognition for this mostly unpaid work is extremely limited, consisting of inconsistently applied yearly letters acknowledging peer reviews completed. Letters for other tasks are only available upon request, with academics typically asking for them to account for their broader contribution to the research landscape as part of their continual professional development. These letters can be delayed, lost or forged and are an administrative burden for the NIHR. In short, they are an inadequate means of recognition relative to the contribution of those who provide their time to advance the NIHR’s research portfolio.

These problems of recognition extend to other funders and the wider scientific community. Reviewing, advising, assessing and reporting all require a significant time and intellectual investment but are not formally captured. Consequently, this work does little to aid career advancement or grant funding, potentially reducing academic interest and engagement in these critical activities that support scientific progress. For funders, this can result in slower and lower quality grant assessment, delayed funding of good research and sloppy work slipping through systems meant to ensure checks and balances (Trovò and Massari, 2021). Current metrics also heavily discriminate against those who take career breaks, particularly women taking time off to have children (Swider-Cios et al., 2021). Recognition systems, therefore, need to change to ensure good and quality research, to foster a healthy and sustainable scientific ecosystem, and for academics themselves (Tite and Schroter, 2007; Warne, 2016; Grant, 2021; Terheggen, 2021; Trovò and Massari, 2021).

Tokens can be awarded for any number of activities but generally they should match the core and regular work of the funding organisation. For example, tokenising peer review makes more sense than tokenising reporting if the awarding organisation does lots of peer review and not much reporting. In Phase 1, the pilot, we plan to award tokens for six distinct and binary tasks (Table 1). These represent core NIHR work and were developed through extensive collaboration with NIHR staff and external academics.

Moving past Phase 1 and into the wider evaluation and deployment of Phase 2, a new range of tokens would be introduced (Table 2) to complement the core tokens described in Table 1. These reward a wider range of activities while supporting EDI objectives.

Awarding tokens in separate categories is deliberate as the purpose of this system is to recognise contribution, not ascribe value. If just an “NIHR Token” existed then either a single token would be given for any single task or different numbers of tokens given for different tasks. In both cases it would cause value to be ascribed, either saying all work is equal or making a judgement of how much more valuable one task is than another. Separating tokens into categories and awarding one specific token for each task completed addresses this problem and gives richer data for analysis.

Generally, for an innovative, disruptive blockchain solution to be successful it must be simple and efficient, solving one or two clear problems rather than being overly complex (Kosmarski, 2020). Seamless integration into scientists’ daily workflow, working with existing practice and not making life harder is paramount (Leible et al., 2019; Kosmarski, 2020). Therefore, our system does not assess quality and awarding is binary; if the job is completed to existing quality standards then a token is given. This means there is no additional workload, increasing the likelihood of support and adoption while removing value judgement as mentioned previously, though value assessment and rating could be designed in future iterations if deemed valuable.

Proposed tokens on the NIHR system would not inherently be utility tokens, as they would not be tradable or worth money to avoid creating potential perverse incentives and changing the reasons people carry out roles. Instead, the goal is they act as a verifiable, immutable, and tangible expression of appreciation and recognition of service completed.

The token’s utility will be as a validated transaction history of scientific contributions for use in professional assessments such as job interviews, award and funding applications, performance appraisals, and academic file review, where currently such records of work are less quantifiable and may lack validity. For senior researchers, tokens may have less perceived value in interviews (as they will be assessed on different criteria by employers) however token status could bolster personal award applications such as the NIHR Senior Investigator Award, where a key element of selection is “contribution to the NIHR” ²⁰ . For more junior researchers, validation of these scientific contributions can directly support favourable hiring and promotion decisions as academic service remains an element for file review and those early in their career need to differentiate themselves. For scientists who are looking to transition to non-academic careers in industry, non-profits or the government, such digital assets and proof of service can also assist in translation of technical skills outside of academia.

Many hurdles come down to public perception. The regular negative media portrayal of cryptocurrency may tarnish the reputation of blockchain regarding its application to academic and scientific processes. The lack of understanding which causes this is the root of much of the scepticism, confusion and fear that blockchain attracts. When the basics are understood but little known about the practical applications it is often judged to be an indulgent new technology which sounds useful but is “not for us” (Kosmarski, 2020). For our system, it is primarily academics, their employers, their professional bodies and those working for research funders who will need to be won over. To do this, a programme of engagement and communication will need to be deployed to promote understanding and dispel misconceptions. To aid buy-in, our solution is not aiming to reshape an entire ecosystem, as many proposals do (Janowicz et al., 2018; Mackey et al., 2019a). A complex and fundamental shift requires the support of many stakeholders, a difficult feat to achieve (Kosmarski, 2020). Instead, we aim to solely address the problem of recognition, evident to thousands of researchers, and integrate our solution into current practices as seamlessly as possible.

Tension between blockchain technologies and General Data Protection Regulation (GDPR) exist, primarily relating to the data controller, data minimization, purpose limitation and perhaps most pertinently, erasure of data (European Parliament, 2019). Given different types of blockchain technology can have very different characteristics, coupled with conceptual uncertainty about GDPR itself, it makes this problem complex and situation dependent. While there is conflict between the two, a general relationship cannot be established and therefore must be determined on a case-by-case basis. Consequently, compliance needs to be designed into the system framework from the beginning to overcome data protection hurdles (European Parliament, 2019; Zemler & Westner, 2019; Casino et al., 2020).

Despite these issues, progress has been made, especially around data erasure. One of the most cited approaches is to store part of the data off-chain, linked with a hash, address or other identifier. By destroying this linking information, the data residing on the chain would be rendered unidentifiable (Haque et al., 2021; EU Blockchain Observatory and Forum, 2022). What’s more, blockchain can intrinsically improve data management practices by helping track the flow of personal data, while being compliant itself (Al-Zaben et al., 2018).

We suggest that by using the off-chain method our system could remain GDPR compliant. Only token status and associated wallet address (an alphanumeric string analogous to an email address identifying the location to which tokens are sent) would be published on a public blockchain. Stored off-chain would be the association between names and wallet addresses. A separate micro-site would associate the public chain with the off-chain database in order to identify an individual’s token status. This would be visible in its entirety to the funder awarding tokens however each academic would only be able to view their own record. The individual would then be able to share this with third parties should they wish. To erase someone’s data the awarding funder would simply have to delete the off-chain association between wallet address and individual to render the data unidentifiable.

A risk remains that a sufficiently motivated and skilled actor who had previously been given the wallet address could search a block explorer (such as Etherscan ²² ) for that specific address and match up the data. This, however, does not pose a significant risk as the chance of it happening is low, the data that could be extracted is very limited and the wallet address would have been shared by the academic themself.

The main limitation of this approach is that by attempting to extensively incorporate GDPR requirements a single trusted party is introduced (the funder which holds the off-chain database). The private data this party holds weakens the decentralised and open benefits of blockchain, given the fact you need to refer to this off-chain information in order to link the individual to their tokens. This seems to be a necessary compromise, however, as a true public, permissionless blockchain is likely to come into significant conflict with GDPR (Zemler & Westner, 2019).

If we cannot ascribe meaningful value to the tokens the system may not be used as intended, the benefits could be unrealised and behaviour not driven as desired. This risk exists as these tokens do not hold intrinsic value, but rather are a representation of work done. To overcome this a combination of interventions may be needed, including but not limited to: 1) generating education and awareness about the purpose of the token and its utility in providing a verifiable record of accomplishments relative to existing incomplete and unverifiable sources of information (e.g., traditional CV, website profiles, etc.); 2) adoption of tokens into research and funding evaluation and assessment; and 3) integration of recognition tokens into university and employer professional development, assessment, and promotional policies and practices.

A new incentive scheme always risks unintended consequences and people may try to exploit it; in our case it risks changing the reasons people carry out work. To mitigate this the tokens would not be worth money or be exchangeable for any specific opportunities, in other words they have no “active” use. This serves two purposes. Firstly, it disincentivises fraud, given that the token’s value is simply a validated record of work performed and is generated by consensus from the issuing organisation (e.g., the funder). Hence, the opportunity for fraud and the utility of engaging in misleading or fraudulent activity is greatly diminished. Secondly, the multiple token categories mean not all work is classed as the same, preventing people from doing the most straightforward job they can just to earn the maximum number of tokens. Furthermore, tasks cannot just be done at the academic’s wish, they have to be invited, this removes the opportunity to ‘mine’ the system for as many tokens as possible.

An expanded system with a wider range of tokens along with greater levels of automation and integration provides huge potential for system improvements, cost savings and efficiency making, particularly by using smart contracts as previously discussed. For example, when a potential reviewer accepts the application review request then a smart contract could automatically inform them of the requirements such as deadline, writing structure and conflict of interest policy. Once a valid review is submitted that meets the conditions of the smart contract then the tokens could be released automatically to the individual. If the review is late then tokens could be withheld and an automated email reminder sent to inform that the review is due (Mackey et al., 2019a). Linking this with current, established academic recognition systems such as ORCID provides the opportunity for greater integration and reach. Alongside this, a future possibility is to enable a more active use of tokens, as discussed in Section 2.2. This may involve allowing token holders to undertake specific activities such as participation in workshops, research prioritisation and evaluation of grant proposals (Ducrée, 2020).

A future system should also reward public contributors (patients and members of the public who are involved in research). Awarding them with the same tokens given to academics would reinforce their equal status, provide a formal record of their contribution and complement the reward payments they currently receive. This would help continue the drive to put patients and the public at the centre of everything the NIHR does.