FAIR Principles

Overview

The FAIR Principles are 15 guiding principles for scientific data management and stewardship, published in 2016 by Wilkinson et al. in Scientific Data (DOI:10.1038/sdata.2016.18). FAIR stands for Findable, Accessible, Interoperable, and Reusable. They are not a standard or a certification — they are a set of aspirational properties that data and metadata should have to maximise their value for both humans and machines. The principles emerged from a Lorentz Center workshop in Leiden in January 2014, with a first draft circulated through the FORCE11 community and refined over almost two years before formal publication. They are now mandated by most major European and national research funders, including the EU Horizon Europe programme, France’s ANR, and many others worldwide.

The 15 Principles

Findable

• F1: Data and metadata are assigned a globally unique and persistent identifier
• F2: Data are described with rich metadata
• F3: Metadata clearly and explicitly include the identifier of the data they describe
• F4: Data and metadata are registered or indexed in a searchable resource

Accessible

• A1: Data and metadata are retrievable by their identifier using a standardised communications protocol; the protocol is open, free, and universally implementable
• A1.1: The protocol allows for an authentication and authorisation procedure where necessary
• A1.2: The protocol allows for access to metadata even when data are no longer available
• A2: Metadata are accessible even when the data are no longer available

Interoperable

• I1: Data and metadata use a formal, accessible, shared, and broadly applicable language for knowledge representation
• I2: Data and metadata use vocabularies that follow FAIR principles
• I3: Data and metadata include qualified references to other data and metadata

Reusable

• R1: Data and metadata are richly described with a plurality of accurate and relevant attributes
• R1.1: Data and metadata are released with a clear and accessible data usage licence
• R1.2: Data and metadata are associated with detailed provenance
• R1.3: Data and metadata meet domain-relevant community standards

Connections

• Maturity model: RDA (FAIR Data Maturity Model, 2020)

Resources

• https://www.go-fair.org/fair-principles/
• Wilkinson et al. (2016) Nature Scientific Data DOI:10.1038/sdata.2016.18
• https://www.rd-alliance.org/group/fair-data-maturity-model-wg (RDA Maturity Model)
• https://www.nature.com/articles/s41597-022-01710-x (FAIR assessment review, 2022)