FAIR

FAIR principles

Findable, Accessible, Interoperable, Reusable (FAIR) principles are a set of guidelines for making research outputs easier to discover, access, combine, and reuse. FAIR is not only about publishing files. It is about exposing enough structure and context that both humans and machines can understand what a dataset, software package, workflow, or research claim represents.

The four principles

1. Findable: Research objects should be discoverable through persistent identifiers, descriptive metadata, and searchable registries.
2. Accessible: The data or metadata should be retrievable through stable and well-documented access methods, even when the full object itself has restrictions.
3. Interoperable: Data should use shared formats, vocabularies, and conventions so they can be combined across tools and disciplines.
4. Reusable: The object should include enough provenance, licensing, and methodological context for someone else to interpret and reuse it correctly.

Why FAIR matters in climate research

Climate workflows routinely combine observations, reanalysis products, model output, and derived diagnostics. Without strong metadata and shared conventions, those pieces become difficult to compare or reproduce. FAIR principles help reduce that friction by making variables, units, coordinates, provenance, and licenses explicit.

In this garden

In this vault, FAIR is the umbrella concept linking data standards, metadata practice, and machine-actionable knowledge representation.

• ATMODAT translates FAIR expectations into atmospheric-data guidance.
• UC2 data standard applies structured metadata and variable conventions to research workflows.
• Metadata provides the descriptive layer that makes research objects understandable.
• Provenance explains where a result came from and how it was produced.
• Open Research Knowledge Graph extends FAIR ideas toward structured representation of research claims.

Common misunderstanding

FAIR does not necessarily mean fully open. A dataset can remain access controlled and still be FAIR if its metadata, access conditions, and provenance are clearly documented.

See also: ATMODAT, UC2 data standard, Metadata, Provenance, Open Research Knowledge Graph, MOC Open Science Data and Knowledge Graphs