Network Meeting - 10 February 2026
- Arie Baak
- Apr 9
- 2 min read
TOPICS
The networking meeting of the 9th of December covered the following topics:
Welcome
Introductions
FAIR Implementation Guidance approach - update (Barend)
Desci Labs starter kit presentation
FAIR enough questionnaire
Parking lot & close
SUMMARY
Introduction - Barend Mons
The FAIR Implementation Guidance (FIG) approach — which structures FAIRification around four progressive levels of data use, from personal to fully machine-actionable data visiting — is gaining traction. Several organizations have already used it to shape funding proposals, and a recent submission for the African Open Science Platform was completed in collaboration with LIFES. The Pistoia Alliance confirmed strong alignment with their FAIR Maturity Matrix, and closer collaboration is planned. The LIFES starter kit now includes sandbox offerings from eleven member organizations, covering data stations, analytics platforms, verification tools, and training. On the policy front, FAIR data features prominently in the Dutch Digital Holland strategy agenda — with LIFES explicitly mentioned in documents submitted to government — and a €170M budget for making Dutch data AI-ready has been proposed for 2026.
LIFES Starter KIT presentation - DeSci Publish platform by DeSci Labs
DeSci Labs presented DeSci Publish, a platform that simplifies FAIR metadata generation for researchers. Uploading any research artifact — data, code, figures, or PDFs — triggers automatic extraction of core metadata and generation of a structured RO-crate, with AI adding keywords, related articles, and a novelty score. A FAIR evaluation badge is under development with the FAIR2ADAPT project. The platform is built on the Codex Protocol, which uses content-based identifiers rather than URLs, preventing link rot and content drift — conceptually similar to nanopublications. Storage runs on IPFS, with DeSci Labs based in Switzerland. The sandbox tier is free up to 100 GB and works for any document type, not only scientific articles.
'FAIR Enough' Questionnaire
A draft questionnaire structured around the four FAIR maturity levels was reviewed collectively. It guides organizations through a progressive self-assessment — from minimal personal use through to full machine-actionable compliance — and is designed to pre-fill portions of the Data Stewardship Wizard and FIB Wizard, reducing duplication. Discussion concluded that domain identification (who you are, what data you hold, what you want to achieve) should precede the questionnaire, with AI-assisted inference helping route users to the right FAIR Implementation Profile and semantic models automatically. The next step is translating the finalized question list into a wizard data model.
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