https://www.openaire.eu/how-to-make-your-data-fair
The FAIR principles ensure research data is managed in a way that makes it easy to find, access, integrate, and reuse. Applying FAIR principles from the start of your project will help you meet funder requirements, increase the visibility of your research, and ensure your data remains valuable long after your project ends.
https://libereurope.eu/wp-content/uploads/2017/12/LIBER-FAIR-Data.pdf
Practical Actions for Researchers
| Principle | What it Means | Example Action |
|---|---|---|
| Findable | Data must have identifiers and rich metadata | Assign a DOI via Zenodo; use clear file names (YYYYMMDD_Project_V1.0). |
| Accessible | Metadata remains visible even if data is restricted | Upload metadata to a repository with licensing and access conditions noted. |
| Interoperable | Use standard vocabularies and file formats | Save in CSV instead of XLSX; use controlled vocabularies (e.g., ORCID for names). |
| Reusable | Data should be documented, licensed, and preserved | Provide a README/data dictionary; add a CC BY licence; include persistent identifiers. |
The Australian Research Data Commons’ FAIR data self assessment tool.
Using this tool you will be able to assess the ‘FAIRness’ of a dataset and determine how to enhance its FAIRness (where applicable).
You will be asked questions related to the principles underpinning Findable, Accessible, Interoperable and Reusable (FAIR). Once you have answered all the questions in each section you will be given a ‘green bar’ indicator based on your answers in that section, and when all sections are completed, an overall ‘FAIRness’ indicator is provided.
https://ardc.edu.au/resources/working-with-data/fair-data/fair-self-assessment-tool/
The Four Basics of FAIR
'Findable' i.e. discoverable with metadata, identifiable and locatable by means of a standard identification mechanism
'Accessible' i.e. always available and obtainable; even if the data is restricted, the metadata is open
'Interoperable' i.e. both syntactically parseable and semantically understandable, allowing data exchange and reuse between researchers, institutions, organisations or countries; and
'Reusable' i.e. sufficiently described and shared with the least restrictive licences, allowing the widest reuse possible and the least cumbersome integration with other data sources.
https://www.openaire.eu/how-to-make-your-data-fair
Aligns with funder policies (Horizon Europe, HRB, IRC).
Increases visibility and citation of your datasets.
Saves time and resources by enabling reuse.
Builds trust in your research.
"Turning FAIR into reality: Final Report and Action Plan from the European Commission Expert Group on FAIR Data" (2018)
https://ec.europa.eu/info/sites/info/files/turning_fair_into_reality_0.pdf
"Guidelines on FAIR Data Management in H2020" (2016)
Data Management Expert Guide, including FAIR Data.
✅ Have you assigned identifiers (DOI, ORCID)?
✅ Is your metadata visible, even if data is restricted?
✅ Are your file formats open and standardised?
✅ Have you included documentation and a licence?