Deciphering Decentralized Science (DeSci): Web3 is laying the groundwork for open science

Decentralized Science (DeSci) is a movement to build a public infrastructure for funding, creating, reviewing, crediting, storing, and disseminating scientific knowledge fairly and equitably using Web3 tools.

DeSci aims to create an ecosystem that inspires scientists to share their research and work openly, while allowing anyone to easily access and contribute to research. DeSci’s philosophy is that scientific knowledge should be accessible to everyone and the process of scientific research should be transparent. DeSci is creating a more decentralized and distributed model of scientific research, making it more resistant to censorship and control by central authorities. DeSci hopes to create an environment in which new and unconventional ideas can flourish by decentralizing funding, scientific tools, and communication channels.

Decentralized science allows for more diverse funding sources (from DAOs, quadratic funding to crowdfunding, etc.), more accessible data and methods, incentives for reproducibility, and more.

How DeSci Improves Science

An Incomplete List of Key Problems in Science and How Decentralized Science Addresses Them

Fund allocation:

DeSci: Funding allocations are determined by the public using mechanisms such as quadratic funding or DAOs.

CeSci: Small, closed, centralized groups control the distribution of funds.


DeSci: Collaborate with peers from around the world in a dynamic team.

CeSci: Funding organizations and bureaucracies limit cooperation.

Decision-making mechanism:

DeSci: Funding decisions are online and transparent. Explore new funding mechanisms.

CeSci: Long turnaround time and limited transparency for funding decisions. Few funding mechanisms exist.

Shared research resources:

DeSci: Sharing lab services made easier and more transparent using Web3 primitives.

CeSci: Sharing lab resources is often slow and opaque.

access permission:

DeSci: New publishing models can be developed that use Web3 primitives for trust, transparency, and universal access.

CeSci: Often published through established channels that are inefficient, biased, and exploitative.

Peer review:

DeSci: Tokens and reputation can be earned through peer-reviewed work.

CeSci: Peer review work is pro bono, for-profit publishers benefit.


DeSci: Owns the intellectual property (IP) generated and distributes it under transparent terms.

CeSci: The institution owns the researcher’s IP, and the access to the IP is not transparent.


DeSci: Share all research, including unsuccessful data, by putting all steps on-chain.

CeSci: Publication bias means that researchers are more inclined to share experiments with successful results.

Ethereum and DeSci

Decentralized scientific systems will require strong security, minimal currency and transaction costs, and a rich application development ecosystem. Ethereum provides everything needed to build a decentralized scientific stack.

DeSci use case

DeSci is building a scientific toolset to bring Web2 academia into the digital world. The following are examples of use cases that Web3 can provide the scientific community.


Scientific publishing is notoriously problematic because it is run by publishers, relying on the free labor of scientists, reviewers, and editors to generate papers, and then charging exorbitant publishing fees. The public usually pays for the work and publication indirectly through taxes, and they often cannot access the same work without paying the publisher again. The total cost of publishing an individual scientific paper is often in the five figures (dollars), undermining the entire notion of scientific knowledge as a public good, while generating huge profits for a small group of publishers.

Free and open access platforms exist in the form of preprint servers such as ArXiv. However, these platforms lack quality control and anti-witch mechanisms, and often do not track article-level metrics, meaning they are often only used to promote work before submission to traditional publishers. SciHub also allows free access to published papers, but not legally, and only after publishers have charged a fee and incorporated the work into strict copyright legislation. This leaves a critical gap for accessible scientific papers and data with embedded legitimacy mechanisms and incentive models. The tools to build such a system exist in Web3.

reproducibility and reproducibility

Reproducibility and reproducibility are the foundation of high-quality scientific discovery. Repeatable results can be obtained multiple times in a row by the same team using the same method. Reproducible results can be achieved using different groups of the same experimental setup. New Web3 native tools ensure that reproducibility and reproducibility are the foundation of discovery. We can integrate quality science into the technical fabric of academia. Web3 provides the ability to create proofs for each analytical component: raw data, computational engines, and application results. The beauty of consensus systems is that when a trusted network is created to maintain these components, each network participant can be responsible for replicating computations and verifying each result.


The current standard model for funding science is for individuals or groups of scientists to submit written applications to funding agencies. A small group of trusted individuals grade applications, then interview candidates and allocate funds to a small group of applicants. In addition to creating bottlenecks that sometimes lead to years of waits between applying and receiving funding, this model is highly susceptible to review panel biases, self-interest and politics.

Research shows that grant review panels do a poor job of selecting high-quality proposals, as the same proposals submitted to different panels can produce wildly different results. As funding has become more scarce, it has been concentrated into a smaller pool of more senior researchers who tend to be more intellectually conservative projects. This effect creates a competitive financing environment, cements perverse incentives and stifles innovation.

Web3 has the potential to disrupt this broken funding model by extensively experimenting with different incentive models developed by DAOs and Web3. Traceable public goods funding, quadratic funding, DAO governance, and tokenized incentive structures are some of the Web3 tools that could revolutionize science funding.

Intellectual Property Ownership and Development

Intellectual property (IP) is a big problem in traditional science: from being stuck in universities or not being used in biotechnology, to notoriously hard to value. However, ownership of digital assets such as scientific data or articles is something Web3 does very well with NFTs.

Just as NFTs can give revenue from future transactions back to the original creator, you can build transparent value attribution chains that reward researchers, governing bodies (like DAOs), and even those who collect data.

IP-NFTs can also serve as the linchpin of a decentralized data repository for ongoing research experiments and plug into NFTs and DeFi financialization (from fragmentation to loan pools and valuation). It also allows native on-chain entities like DAOs like VitaDAO to conduct research directly on-chain. The emergence of non-transferable “soul-bound” tokens may also play a major role in DeSci, allowing individuals to attest to their experience and credentials associated with their Ethereum addresses.

Data storage, access and architecture

Using Web3 schemas can make scientific data more accessible, and distributed storage will allow research to survive catastrophic events.

The starting point must be a system accessible to any decentralized identity holding appropriate verifiable credentials. This allows trusted parties to securely replicate sensitive data, enabling redundancy and censorship resistance, reproducibility of results, and even multi-party collaboration and the ability to add new data to datasets. Confidential computing methods such as compute-to-data provide alternative access mechanisms for raw data replication, creating a trusted research environment for the most sensitive data.

Flexible Web3 data solutions support the above scenarios and lay the foundation for true open science, where researchers can create public goods without access rights or fees. Web3 public data solutions like IPFS, Arweave, and Filecoin are optimized for decentralization. For example, dClimate provides universal access to climate and weather data, including data from weather stations and predicted climate models.

Posted by:CoinYuppie,Reprinted with attribution to:
Coinyuppie is an open information publishing platform, all information provided is not related to the views and positions of coinyuppie, and does not constitute any investment and financial advice. Users are expected to carefully screen and prevent risks.

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