Measuring FAIR Principles to Inform Fitness for Use

Abstract

For open science to flourish, data and any related digital outputs should be discoverable and re-usable by a variety of potential consumers. The recent FAIR Data Principles produced by the Future of Research Communication and e-Scholarship (FORCE11) collective provide a compilation of considerations for making data findable, accessible, interoperable, and re-usable. The principles serve as guideposts to ‘good’ data management and stewardship for data and/or metadata. On a conceptual level, the principles codify best practices that managers and stewards would find agreement with, exist in other data quality metrics, and already implement. This paper reports on a secondary purpose of the principles: to inform assessment of data’s FAIR-ness or, put another way, data’s fitness for use. Assessment of FAIR-ness likely requires more stratification across data types and among various consumer communities, as how data are found, accessed, interoperated, and re-used differs depending on types and purposes. This paper’s purpose is to present a method for qualitatively measuring the FAIR Data Principles through operationalizing findability, accessibility, interoperability, and re- usability from a re-user’s perspective. The findings may inform assessments that could also be used to develop situationally-relevant fitness for use frameworks.