The Four Basics of FAIR:
The four basics of FAIR (in practice, FAIR applies to both data and metadata):
| 'Findable' | i.e. described with rich metadata, assigned a globally unique and persistent identifier (PID), and indexed/registered so that people and machines can discover and reliably reference it. |
| 'Accessible' | i.e. retrievable by its identifier using standardized communication protocols; access can be open or restricted (authentication/authorization are allowed), but metadata should remain accessible even when data are no longer available. |
| 'Interoperable' | i.e. described using formal, shared languages, community standards, and controlled vocabularies/ontologies, and includes qualified links to related (meta)data so that systems can integrate and exchange information across tools, institutions, and borders. |
| 'Reusable' | i.e. richly described with accurate context, includes clear usage licenses, and records provenance, while aligning with domain-relevant community standards, enabling maximum lawful and meaningful reuse. |
FAIR in the European ecosystem: FAIR is increasingly implemented through PID-enabled connections (e.g., DOIs for outputs, ORCID iDs for people) that support discovery and linking in PID Graph / Research Graph services used in EOSC-era infrastructures.
Things to remember
FAIR is a set of principles; not a standard, specification, or binary label. You can improve FAIRness incrementally as your workflows and infrastructure mature.
Does following the FAIR principles mean your data must be shared openly with everyone? NO. Data can be FAIR but not open: FAIR explicitly supports scenarios where metadata are open and informative while access to the data is controlled for legitimate reasons (e.g., privacy, safety, IP, contractual constraints).
Open data may not be FAIR: data can be publicly available yet still hard (or impossible) to reuse if it lacks persistent identifiers, sufficient metadata, standards, provenance information, or an explicit license.
If you are in receipt of Horizon Europe funding and your project participates in the Open Research Data Pilot, a DMP is required, with a first version within the first six months, and it should be updated when significant changes arise.
Under Horizon Europe, responsible RDM aligned with FAIR is part of mandatory open science practice; a DMP should be a living document delivered by month 6 and updated as the project evolves, and open access to research data follows the principle “as open as possible, as closed as necessary.”
OpenPlato course: FAIR Research Data Management: A Practical Introduction by PATTERN project