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FAIR data is data which meets the FAIR principles of findability, accessibility, interoperability, and reusability (FAIR). [ 1 ] [ 2 ] The acronym and principles were defined in a March 2016 paper in the journal Scientific Data by a consortium of scientists and organizations.
3. Access/Participation [14] Access as defined in the Fair Information Practice Principles includes not only a consumer's ability to view the data collected, but also to verify and contest its accuracy. This access must be inexpensive and timely in order to be useful to the consumer.
Following the specification facilitates the documentation of privacy requirements from software conception to retirement, thereby providing a plan around adherence to privacy by design principles, and other guidance to privacy best practices, such as NIST's 800-53 Appendix J (NIST SP 800–53) and the Fair Information Practice Principles (FIPPs ...
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Large-scale learning assessments (LSLAs) is defined as a form of national or cross-national standardized testing that provide a snapshot of learning achievement for a group of learners in a given year and in a limited number of learning domains. [1] [2] The use of these assessments have been increasing around the globe and have also broadened ...
The FAIR principles have immediately been coopted by major international organization: "FAIR experienced rapid development, gaining recognition from the European Union, G7, G20 and US-based Big Data to Knowledge (BD2K)" [46] In August 2016, the European Commission set up an expert group to turn "FAIR Data into reality". [47]
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FAIR is an acronym for 'findable, accessible, interoperable and reusable', intended to more clearly define what is meant by the term 'open access' and make the concept easier to discuss. [ 47 ] [ 48 ] Initially proposed in March 2016, it has subsequently been endorsed by organisations such as the European Commission and the G20 .