FAIR, not necessarily “open”

The FAIR principles say data should be Findable, Accessible, Interoperable, and Reusable. Note: FAIR is about good stewardship, not forced openness — sensitive data can be FAIR yet access-controlled (“as open as possible, as closed as necessary”).

Worked example — making a dataset FAIR
F: deposit in a repository so it has a DOI and metadata. A: a clear access route (open, or by request). I: use standard formats (CSV) and vocabularies. R: add a README and a licence. The same dataset is now far more valuable to others — and to future you.

🔗 Learn more (free): Digital Curation Centre — how-to guides on FAIR data

Try it
Take a dataset you know. Score it F-A-I-R: which letter is weakest, and what one step would improve it?

Self-check

What does “as open as possible, as closed as necessary” mean for sensitive data?

© FRELIP, released under CC BY 4.0. Adapted in part from openly-licensed UNESCO (CC BY-SA 3.0 IGO) and institutional research-support materials. Linked resources remain under their own licences. Curated by the FRELIP Open Courseware editorial team.

Modifié le: jeudi 4 juin 2026, 12:52