FAIR principles
Also: FAIR data · Findable, Accessible, Interoperable, Reusable
Four principles for research data — Findable, Accessible, Interoperable, Reusable — now widely expected in research funding and data management plans.
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The FAIR principles, set out by Wilkinson and colleagues in Scientific Data in 2016, ask that research data be Findable (a persistent identifier and rich description), Accessible (retrievable in a standard way, with the description surviving even if the data do not), Interoperable (in shared formats and vocabularies) and Reusable (with a clear licence and a record of how the data were made). They stress that machines, not only people, should be able to find and use the data.
Why it matters for your research. A collection of transcribed periodicals is research data, and most data management plans now ask how it will meet FAIR. Meeting them is what lets the collection outlast the project that built it, and lets another scholar check, cite and extend your work. FAIR is about usability, not openness: data can be FAIR and still restricted, for good reasons of rights or of community consent.
In Archēglyph. A collection is saved as fixed editions, each with its own permanent link, which makes it findable; persistent identifiers (DOIs) for editions are next on the project roadmap. Published collections are public, and any edition downloads whole, which makes it accessible. The formats are open and documented, which makes it interoperable. Each edition records what read, translated and grouped it, and carries a licence chosen by its owner, which makes it reusable. The method page sets out where this falls short.
Not to be confused with. Open data, which is about who may use data, not whether it can be found and reused. And the CARE principles, which complement FAIR by asking whom data serves and who decides.