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AI & Foundations

FAIR Data Principles

Findable, Accessible, Interoperable, Reusable: four properties that make data useful to others and to your future self.

Four Properties

The FAIR principles state that research data should be Findable, Accessible, Interoperable, and Reusable. They target not the correctness of data but its usefulness: data that cannot be found, obtained, combined, or understood is data that only its creator can use, and often not even them a year later.

What Each Means

Kronos motion — data assimilation

Metadata Is the Point

Much of FAIR is really about metadata, the description of the data: what each field means, in what units, collected how, under what conditions. Data without metadata is uninterpretable no matter how accessible. Persistent identifiers, stable references that do not rot like ordinary web links, make findability durable over time.

FAIR Is Not Open

FAIR does not require data to be public. Access can be controlled; the principle is that the terms of access are clear and the metadata discoverable. This distinction matters where data are sensitive or restricted: they can still be FAIR by being well described, uniquely identified, and accessible under stated conditions to those authorized.

In Practice

Depositing data in a repository that issues persistent identifiers, with a clear license and complete metadata, satisfies much of FAIR. Kronos physics deposits carry persistent identifiers and documentation so that published results can be located, retrieved, and reused correctly by independent parties, while confidential material stays outside the public repositories entirely.