Definition of FAIR Data
To make data easier to share and reuse, researchers and data scientists try to align with the FAIR data principles.
FAIR data is:
- Findable: For data to be findable there must be sufficient metadata; there must be a unique and persistent identifier; and the data must be registered or indexed in a searchable resource.
- Accessible: To be accessible, metadata and data should be readable by humans and by machines, and it must reside in a trusted repository.
- Interoperable: Data must share a common structure, and metadata must use recognized, formal terminologies for description.
- Reusable: Data and collections must have clear usage licenses and clear provenance, and meet relevant community standards for the domain.
Which is the main FAIR principle demonstrated by the below practices?
- Describing the subjects in a biomedical dataset using Medical Subject Headings (MeSH) or SNOMED.
- Submitting the description of a clinical trial to ClinicalTrials.gov.
- Using a well-known data repository like GenBank or PubChem.
- Clearly stating and posting the usage permissions with a dataset.
Wilkinson, M. D. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018. doi:10.1038/sdata.2016.18