Are my data FAIR? A self-assessment in 20 questions
In about 3 minutes, see where a dataset stands against the FAIR principles: data that are findable, accessible, interoperable (readable by other software) and reusable. Twenty questions, five per letter; the tool gives a score out of 20 and shows what to work on first.
Who is it for? PhD students, researchers, engineers and data stewards preparing a deposit, a data management plan (DMP, the document that describes how the data of a project will be produced, described, stored and shared) or a publication. Three prefilled examples serve as starting points, including Webservice-Energy, the data infrastructure of the O.I.E. center (Observation, Impacts, Energy) at Mines Paris – PSL. Nothing is sent anywhere: your answers stay in your browser.
Is my project FAIR enough? An example of a 20-point self-assessment
This is only an example: a teaching grid proposed here, not a standard or a certification. The questions follow the GO FAIR principles (F1 to R1.3) plus a few practical criteria; the scoring and thresholds are choices of this page. For a reference assessment: the RDA FAIR Data Maturity Model (Research Data Alliance) or the automated tool F-UJI. Acronyms underlined with dots open an explanation on click or tap.
Five questions per letter, from the most basic to the most demanding; each "yes" is worth 1 point, "partly" 0.5. Total out of 20. Benchmarks: below 5: needs work; 5 to 10: good; above 10: very good. The tool names the axes to work on and, above 10, the limiting factor: the weakest letter, which bounds real reuse.
Webservice-Energy: which component serves which principle?
| Component | F | A | I | R |
|---|---|---|---|---|
| GeoNetwork (CSW) | F | A | R | |
| GeoServer (WMS, WCS) | A | I | ||
| THREDDS / OPeNDAP / NCSS | A | I | R | |
| Toolbox & S3P2 (WPS) | I | R | ||
| STAC (REST) | F | A | I | |
| libinsitu | I | R | ||
| DOI landing pages | F | R | ||
| NetCDF-CF / Zarr / GeoParquet | I | R |
Mapping drawn up by the Webservice-Energy team (O.I.E. center): each open component covers part of the principles; together they cover them all.
Indicative self-assessment based on the GO FAIR principles (F1 to R1.3); it does not replace a data management plan (written for example with DMP OPIDoR) or the advice of your institution's data service. Your answers stay in your browser.
Why this grid?
This is only a teaching example, not a standard or a certification. The twenty questions follow the FAIR principles published by Wilkinson et al. (2016) and promoted by the GO FAIR initiative (F1 to F4, A1 and A2, I1 to I3, R1.1 to R1.3), plus a few practical criteria. The scoring (1 point for “yes”, 0.5 for “partly”, 0 otherwise) and the thresholds (5 and 10 out of 20) are choices made for this page: they help you learn what makes data reusable, not rank projects.
For a reference assessment, use:
- the RDA FAIR Data Maturity Model (Research Data Alliance, the international organization that develops recommendations for sharing research data): shared indicators and their priority levels;
- F-UJI, an automated tool that assesses a published dataset from its persistent identifier, for example a DOI (Digital Object Identifier, an identifier that stays valid even if the web address changes).
How to cite this tool
Ménard, L., Jolivet, R. and Voyant, C., O.I.E. center, Mines Paris – PSL (2026). FAIR self-assessment of research data: an example teaching grid in 20 questions, version 1.0, November 4, 2026. License: CC BY 4.0 (Creative Commons Attribution: free reuse with credit to the source).
Web address (URL) to cite: https://www.cyrilvoyant.com/tools/fair-self-assessment/
The same reference in BibTeX (the bibliography format of LaTeX):
@misc{oie2026fair,
author = {M{\'e}nard, Lionel and Jolivet, Rapha{\"e}l and Voyant, Cyril},
title = {FAIR self-assessment of research data: an example teaching grid in 20 questions},
year = {2026},
version = {1.0},
howpublished = {Web application},
note = {O.I.E. center, Mines Paris -- PSL. Version 1.0, November 4, 2026. License CC BY 4.0},
url = {https://www.cyrilvoyant.com/tools/fair-self-assessment/}
}Where the grid comes from
The questions and the reference example come from the practice of Webservice-Energy, the data infrastructure of the O.I.E. center: the FAIR approach is that of Lionel Ménard (ORCID), the center's FAIR data lead (lionel.menard@minesparis.psl.eu); the license part follows the reflection of Raphaël Jolivet (ORCID) (raphael.jolivet@minesparis.psl.eu). Cyril Voyant, co-author, shaped the grid and put it online; any transcription errors are his.
Go further: data and licenses
The page Models live in the data explains why data must be qualified and certified, details the example of Webservice-Energy and offers a decision tree to choose a license for code and data.