Science is the process of discovery. It powers technological advancement and enables us to navigate and manipulate our environment. Strong economic, ethical and pragmatic arguments can be made in favour of scientific knowledge being a public good. This is especially true now that damaging disinformation is especially rife yet novel discoveries will be needed to fight existential-level threats like pandemics and climate change. However, this knowledge comes from scientific research, and our current infrastructure for doing that is no longer fit for purpose, from the initial allocation of funds right through to the eventual dissemination of results. The reasons for this are diverse but ultimately share a common thread: they are emergent phenomena of centralized control. In future, a stack of DeSci dapps could offer a more attractive model for altruistically driving, doing and disseminating scientific research. This essay will make the case for DeSci and suggest a potential roadmap for building out a DeSci stack.
The broken TradSci model
Science is enabled by distribution of funds to individuals or groups who propose to complete some specific project. In the general model, written applications are scored by a small panel of individuals who might then interview shortlisted candidates prior to awarding funds to a successful few. This general model has a long history, but is also well-known to be vulnerable to the biases, politics and self-interest of the review panel. There has been shown to be no correlation between grant application scores and their eventual outcomes indicating that review panels do a poor job of selecting high quality projects. The same proposals given to different panels have wildly different outcomes, without even agreement on the relative merits of the proposals. These issues have been amplified as research funding has become more scarce over time, entrenching a “funding crisis“. Funders have increasingly favored “safe hands”, hindering the progression of new researchers and stifling intellectually ambitious projects. The effect has been to circulate money around an established pool of academics, while also creating a hyper-competitive funding landscape that incentivizes applicants to over-promise and under-deliver. There have been calls to replace the current system with, for example, grant lotteries. Overall, the current centralized funding model is inefficient, entrenches perverse incentives and undermines the scientific progress it is supposed to promote.
Science publishing is also famously problematic in that it relies upon free labour from authors, reviewers and editors, then charges high fees from authors to cover publication costs. The resulting article is then usually hidden behind paywalls so that readers pay to access knowledge that – in the case of nationally funded work – they have already paid for through taxation. Alternatively, authors stump up an inflated “open access fee” to make the article available to the public. This creates a two-level science publishing system – those that can afford to publish open-access in high impact journals (raising their chances of future grant capture and employment) and those that can’t (diminishing their chances of funding and promotion). While free and open-access platforms do exist in the form of pre-print servers (e.g. ArXiv) these platforms lack quality control mechanisms and do not generally track article-level metrics, meaning they are usually used only to publicize work prior to submission to a traditional publisher. SciHub also exists to make published papers free to access, but not legally, and only after the publishers have already taken their payment and wrapped the work in strict copyright legislation.
In order to publish in reputable science journals, articles undergo peer-review. The theory of peer review is that experts in an appropriate discipline examine the work to determine whether it meets the necessary standards to be released to the wider community. At its best, peer review is a constructive process of incremental improvements to a manuscript that strengthens the underlying science. However, all too often it is a heavily politicized process of gatekeeping that favours more powerful players. Peer review often entrenches dogma and is vulnerable to straightforward pettiness (search #reviewer2 on Twitter). “Open Review” has also been attempted many times, but this is wide open for abuse from trolls.
Ultimately these structural problems with science funding and publishing have arisen from centralized control – a small pool of power-players sculpt the scientific landscape and have created a deeply imbalanced industry from what should be a public good.
DeSci :A new vision for science
A decentralised model could be used to rewrite the rules of professional science. “DeSci” could allow communities to decide how to distribute funds, enabling funding of long term ambitious and intellectually adventurous projects, establishing direct connections between donors and researchers, even retro-actively funding or rewarding researchers for impactful discoveries, inventions and products that have proven to be valuable public goods. Part of the reason why “the best minds of [a] generation are thinking about how to make people click ads” is surely that they are properly incentivized to do so – DeSci offers the potential to radically alter how a new generation of great minds are incentivized to tackle major scientific and technological challenges. At the same time, science articles and associated data can be made truly open and accessible, free or almost-free to publish, subject to a completely open and perpetual community review process that dynamically updates the article’s, and by extension the author’s, credentials. To deliver this vision, developers will need a stack of DeSci dapps that connect a user’s scientific activity to their credibility and their unique value-proposition for funders. Such a system could generate a complex and interesting game theory that could stimulate the development of a healthier science infrastructure.
DeSci will necessarily be defined from the ground up, as multiple dapps with specific value-propositions emerge and co-evolve. However, there are some key features that seem likely to emerge, and some initial ideas that could steer the early development. For example, these seem like sensible a priori development guidelines:
- Grants are flexible, with no floor or ceiling on monetary value, end-dates or number of grants awarded, terms that can be updated and options for retroactive funding etc.
- Articles are free or nearly-free to publish and then universally free to access.
- Peer-review of grants and articles is a perpetual community activity
- An individual’s grant, publication and reviewing credentials are quantified and stored on chain, and likely used to weight their individual contributions to votes and peer review.
While DeSci dapps would likely be viewed with some unease among some areas of the scientific community to begin with – especially within my own field of environmental science where the energy consumption associated with PoW is justifiably likely to be a major barrier to adoption until “the merge” – there is also widespread discontent with the current system and an appetite for structural change that suggests a robust DeSci stack could become a popular way to fund and publish new research in the future.
An example of a DeSci system that conforms to these ideals might begin by replacing the primary currency of research scientists – published articles – with NFTs. These NFTs can be minted and owned by the authors, with the actual manuscript and associated code and datasets hosted on IPFS (or another decentralised storage such as Arweave or Filecoin). This NFT is then citable by other researchers when they mint their own NFTs, with the number of citations for each article tracked in the NFT smart contract. Other users can then decide to review the work. They give the paper a score which is aggregated with prior review scores to generate a “trust score” property of the NFT, which is publicly viewable. The aggregated trust score from all of a user’s NFTs, along with information about successful delivery of grants and other relevant activities can then be used to define their personal score. This score can then be used to weight the user’s reviews on other articles and grant applications. Distribution of funds can then occur by DAO-style voting, with additional weight given to voters with higher scores. Further criteria can also be established using thematic tags on the NFTs.
Meanwhile, science funding might well take inspiration from existing grant-awarding DAOs such as Uniswap and Gitcoin. Weighting of an individual’s reviewing power might follow, for example, a quadratic voting model, where their impact is determined by the square root of their total personal score. Funds could come from onboarding traditional funders into crypto (e.g. by allowing deposits of stablecoins into a contract which are then distributed to researchers) or by the DeSci platform generating funds independently, for example by pooling small publication fees into a community escrow which can be parked in a DeFi protocol to generate yield. The former case also relieves traditional funders of the burden of selecting successful candidates as this responsibility is devolved to the community, although they could impose some stipulations such as specific fields of interest etc.
While writing this article I pulled together a very early “proof-of-concept” for a DeSci publishing platform called SciFoundry. So far, SciFoundry is an ERC721 smart contract hosted on the Rinkeby testnet. Users can mint their articles and receive an NFT which can be viewed on Opensea. Anyone can download the full article and its assets using the external URLs in the NFT metadata, or view the article’s citation and trust score metrics via the Opensea listing. When other researchers mint their own articles they provide a list of token IDs in place of a reference list. This is used by the contract to increment the citation counter of each cited article, updating their stats. Reviewers can also provide numeric scores (/100) and links to text comments by calling a simple function of the SciFoundry contract. The arithmetic mean of all the submitted review scores becomes the NFT’s “trust score” attribute. The project README has more details on the current functionality. This is just the most minimal possible demonstration but it hints at real potential for building out a DeSci stack.
Since publishing an early version of this article online, I have also been pointed to others thinking along similar lines, a nascent “DeSci” community is already growing with web3 at its core.
This article has described the current dysfunctional centralized science infrastructure and provided a loose outline for how DeSci could begin to emerge from the shoulders of DeFi and NFTs. A DeSci stack could be a powerful tool for establishing a fairer and more efficient science landscape that deprioritizes enriching middlemen and reprioritizes the distribution of knowledge as a fundamental public good.