1.6 FAIR Data
In 2016, the data journal Nature—Scientific Data published the FAIR Guiding Principles for Scientific Data Management and Stewardship to clarify and guide researchers with the FAIR principles: Findable, Accessible, Interoperable, Reusable. The FAIR principles pivot around the idea of a continuum of "machine-actionability" in which machines can act autonomously on data objects, (1) in relation to the contextual metadata surrounding a digital object (what is it?), and (2) when referring to the content (how do I process it/integrate it?) (Wilkinson, 2016).
| Principles | Guidelines |
|---|---|
| Findable | 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 | |
| Accessible | 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 | 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 | 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 |