What are the FAIR Data Principles?

Answered By: Julie Goldman
Last Updated: Oct 21, 2022     Views: 6

FAIR is a set of guiding principles that state that data should be findable, accessible, interoperable, and reusable. They address the usability of datasets as well as their availability.

NIH encourages data management and sharing practices to be consistent with the FAIR Data Principles and reflective of practices within specific research communities. In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data. The principles emphasize machine-actionability because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data. 

How do you make data FAIR?

  • To make data findable, data and supplementary materials should have sufficiently detailed descriptive metadata as well as a unique and persistent identifier such as a digital object identifier (DOI).
  • To be accessible, the metadata and data should be understandable to both humans and machines, and data should be stored in a trusted repository.
  • To be interoperable, metadata should use a formal, accessible, shared, and broadly applicable language for knowledge representation, such as agreed-upon controlled vocabularies.
  • To be reusable, data and collections should have a clear usage license and provide accurate information on provenance.

The GO FAIR initiative has provided a more in-depth explanation of FAIR principles.

Top Questions about the NIH DMSP

Related Topics

Still haven't found what you're looking for? Submit your Question