DeSci Publish is an open-source software project that enables publishing, reviewing, and curating research without paywalls or publication fees. It brings manuscripts, code, and data together in one integrated space - making it easy and rewarding to adopt best practices in open science.
By supporting the publish-review-curate model, DeSci Publish accelerates the availability of new insights and enhances transparency in the research process.
With built-in AI tools, DeSci Publish benchmarks manuscripts against a database of 250 million articles, identifies related research, streamlines the submission process, and provides authors with actionable insights to maximize the impact of their work.
Technically, DeSci Publish serves as a graphical user interface for the Collaborative Open Data Exchange (CODEX) protocol—an open scholarly infrastructure for sharing versionable research objects of any file type on a distributed peer-to-peer network. It is also the first scientific publishing solution to harness web3 technologies, advancing openness and accessibility in scientific communication.
On Publish, you can create submission packages with data and code that improve journal publication chances.
You can also upload all milestones of your research project over time to create a fully traceable record of how you reached your results.
For example, start with an analysis plan, add first data and code later, then add a manuscript, and keep updating all files over time without overwriting the original version.
Never forget where you left things off, and get credit for your work long time before you publish in a journal.
When you're ready to submit to a journal, click on "create submission package" and receive a DOI for your research object.
Open science has never been so easy and rewarding!
The Internet was not invented to preserve content for a long time or to ensure its accessibility. That's a problem for the scientific record. DeSci Publish solves these issues.
Based on the CODEX Protocol and IPFS, DeSci Publish uses free-to-use open-source software that cannot be bought or shut down. All content is stored on an open peer-to-peer network that cannot be censored and that enables data sovereignty: Any participant in the IPFS network can pin content from Publish on their servers or devices.
Every version of every file gets an automatic, free, persistent identifier that protects against link rot and content drift, making all content on DeSci Publish findable, accessible, interoperable, and reusable (FAIR) by design.
This new model for persistent identifiers allows you to build versionable research objects for every part of your research, rather than sharing only the final manuscripts. Each research object is indexed, and you can easily update your work in Publish without overwriting earlier versions or breaking any links to the code or data. Never lose files again or forget where you left off.
DeSci Publish is code, data, more than 50 million manuscripts, and unique analytics - all on the open peer-to-peer network for scientific publishing. No more juggling between repositories, preprint servers, and Github. No more paywalls.
Claim open-data or open code badges that, once verified, give you automatic credit on your ORCID profile for having published a dataset or piece of software. Get DOIs for all your work.
Discover related research and receive novelty scores for every version of your uploaded manuscripts
Research is always evolving - let your publications evolve with updated insights and iterative research processes by re-publishing your papers with updates. Old publications remain available in their original form.
Verified badges highlight characteristics of your research that were
checked during peer-review.
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Atharva and Marco created a fully reproducible, data-heavy publication containing over 18 terabytes of open data. Without Nodes, this breakthrough dataset in fluid dynamics would have remained in his lab's internal servers. Nodes made it possible to easily import parts of this dataset with a single line of python, or send a containerised compute job directly to where the data lives.
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