FAIR Principles

The term FAIR originates from the 2014 Lorentz Workshop, which led to 15 guiding principles published in 2016 to make research Findable, Accessible, Interoperable, and Reusable.

The FAIR principles apply to data, metadata, and supporting infrastructure (e.g. search engines). They emphasize machine-actionability — the capacity of computational systems to find, access, interoperate, and reuse data with minimal human intervention.

Findable

The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers.

F1. (Meta)data are assigned a globally unique and persistent identifier.
F2. Data are described with rich metadata (defined by R1 below).
F3. Metadata clearly and explicitly include the identifier of the data they describe.
F4. (Meta)data are registered or indexed in a searchable resource.

Accessible

Once the user finds the required data, they need to know how it can be accessed, possibly including authentication and authorization.

A1. (Meta)data are retrievable by their identifier using a standardized communications protocol.
A1.1. The protocol is open, free, and universally implementable.
A1.2. The protocol allows for an authentication and authorization procedure, where necessary.
A2. Metadata are accessible, even when the data are no longer available.

Interoperable

Data usually need to be integrated with other data, and to interoperate with applications or workflows for analysis, storage, and processing.

I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2. (Meta)data use vocabularies that follow FAIR principles.
I3. (Meta)data include qualified references to other (meta)data.

Reusable

The ultimate goal of FAIR is to optimize the reuse of data. Metadata and data should be well-described so they can be replicated and/or combined in different settings.

R1. (Meta)data are richly described with a plurality of accurate and relevant attributes.
R1.1. (Meta)data are released with a clear and accessible data usage license.
R1.2. (Meta)data are associated with detailed provenance.
R1.3. (Meta)data meet domain-relevant community standards.

References

Wilkinson, M. D., et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018.

The latest developments on FAIR and the full set of principles are available at go-fair.org/fair-principles.