The role of FAIR principles in high-quality research data documentation: Looking at national election studies - Wolfgang Zenk-Möltgen (IASSIST Quarterly)
The FAIR principles as a framework for evaluating and improving open science and research data management have gained much attention over the last years. By defining a set of properties that indicates good practice for making data findable, accessible, interoperable, and reusable (FAIR), a quality measurement is created, which can be applied to diverse research outputs, including research data. There are some software tools available to help with the assessment, with the F-UJI tool being the most prominent of them. It uses a set of metrics which defines tests for each of the FAIR components, and it creates an overall assessment score.