FAIR Data Principles

Originally published in 2016¹ with the goal of defining “good data management” to improve scholarly data with the goal of making downstream use and re-use easier and improve the output of research investments.

In contrast to other initiatives, FAIR data principles place a special importance on making data accessible to machines, not only human consumption (e.g. by making data types discoverable by machines without human intuition).

The principles are not a standard or implementation but a guideline.

The principles

Findability

• 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 it describes
• F4. (meta)data are registered or indexed in a searchable resource

Accessibility

• 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

Interoperability

• 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

Reusability

• 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

Examples

As a concrete example implementation², consider Figshare³:

• Findability: Assigns persistent identifiers (DOIs or Handles) to all research outputs
• Accessibility: Provides access to metadata through standard protocols (https, REST API, OAI-PMH)
• Interoperability: Supports multiple citation metadata formats and controlled vocabularies
• Reusability: Requires clear licensing and maintains detailed versioning for all items

Footnotes

1. Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18 ↩

2. https://guides.library.cmu.edu/researchdatamanagement/FAIR_principles#implementation ↩

3. https://figshare.com/ ↩