FAIR Principles
The FAIR Principles are a set of principles for data and metadata management and stewardship: findability, accessibility, interoperability, and reusability. The acronym was coined by a consortium of scientists and organizations in Scientific Data (2016) to improve the management of digital assets.
For data to be “FAIR,” it must be:
- Findable: Data need to be easy to locate for both humans and computers.
- Accessible: Data need to be accessible to users.
- Interoperable: Data need to integratable with other data and interoperable with applications and workflows for analysis, storage, and processing.
- Reusable: Data need to be well-described so they can be used in different settings.
FAIR emphasizes machine-actionability since data’s increase in volume and complexity has made people more dependent on computational support.
Further Resources
- Data.org (2024) “The FAIR Data Principles”
- Fair Data (Wikipedia)
- GoFAIR (2014) “FAIR Principles”
- Statistics Canada (2022) “FAIR data principles: What is FAIR?” [Video]
- Wilkinson, et al. (2016) “The FAIR Guiding Principles for Scientific Data Management and Stewardship”