The increasing availability of research data and its evolving role as a first class scientific output in the scholarly communication requires a better understanding of and the possibility to assess data quality, which in turn can be described as conformance of data properties to data usability or fitness for use. These properties are multifaceted and cover various aspects related to data objects, access services, and data management processes such as the level of annotation, curation, peer review, and citability or machine readability of datasets. Moreover, the compliance of a data repository or data center providing datasets - for example with certification requirements - could serve as a useful proxy. Firstly, a concept of data fitness requires assessment of quality criteria to be included as well as the weighing of each of those criteria. The process should preferably lead to the development of a corresponding metric. Secondly, we want to find effective ways to expose and communicate this metric, for e.g. by using a labelling or tagging system whereby different usability levels are made explicit.
The Group completed its outputs and recommendations in April 2019 and thus completed its work as a group towards the initial Case Statement. The outputs of this Working Group are considered and included in the efforts of both the FAIR Data Maturity Model WG and the FAIRsFAIR Project.
