FAIR Data

• Data use a formal, accessible, shared, and broadly applicable language for knowledge representation

  • Many disciplines have commonly used standards for language used in data collection. These are sometimes known as metadata schema or controlled vocabulary or might be referred to as a dictionary or thesaurus. Using these accepted standards will make it easier for someone to combine your data with other datasets in the field. You can read more about metadata schema for different disciplines and purposes in the Metadata tab on the Documentation guide.

• Data use vocabularies that follow FAIR principles

  • Ideally, the standard vocabulary you use will have documentation. Even better if that documentation adheres to the FAIR principles. Aim for relatively easy to find documentation and include a citation or link to that documentation in your own documentation. 

• Data include qualified references to other data

  • If you're using multiple data sources, or metadata sources, cite it. This is just good professional practice but also keeps track of all the data sources so that other researchers can understand what your research is showing them. Read more about citing data in the Reusable section of this guide.

To be 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

FAIR Principles definition as referenced from: Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018 doi: 10.1038/sdata.2016.18 (2016).