Short introduction describing any previous activities:
As evidenced by the long list of fields covered by the members of the World Data System (WDS), data from a very diverse set of scientific disciplines are regularly managed by organizations from around the world. Informed decisions on, and accurate (re)use of, individual digital datasets depend on knowledge about the quality of data and relevant information. Effectively representing and communicating dataset quality information is important for conducting research within and across many disciplines, for improving data sharing and ultimately promotes an effective data ecosystem.
As a first step to address this challenge and promote the creation and (re)use of freely and openly shared dataset quality information, international domain experts have undertaken an effort to develop guidelines for the Earth science community. An initiative started with collaboration among the Earth Science Information Partners (ESIP) Information Quality Cluster (IQC), the Barcelona Supercomputing Center (BSC) Evaluation and Quality Control (EQC) team, and the Australia/New Zealand Data Quality Interest Group (AU/NZ DQIG). The guidelines are characterized by practical recommendations to promote sharing and reusing of quality information at the dataset level. A peer-reviewed paper titled “Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets'' was published in the Data Science Journal (DOI:http://doi.org/10.5334/dsj-2021-019), a set of guidelines was developed and described in a white paper (DOI: https://doi.org/10.31219/osf.io/xsu4p), and a BoF session was organized during the last RDA Plenary Meeting (RDA-VP18) to present this work and seek interest in extending it to other disciplines.
Building on the session at P18, the purpose of this BoF is to broaden the disciplinary base covered by these efforts beyond Earth science in promoting consistency when managing dataset quality information. To this end, the European Open Science Cloud (EOSC) FAIR Metrics and Data Quality Task Force has taken a leading role by including perspectives and experiences from diverse disciplines including biology, metrology, philosophy, data and computer sciences. We will focus on common principles, concepts and steps to consider when dealing with quality, as well as identifying the actors involved in the quality assessments and organizations seen as a reference point in each discipline. The endeavor shall form the foundation for comprehensive guidelines in dataset quality across different disciplines to ensure better consistency of metadata sustaining a FAIR interdisciplinary data space.
Additional links to informative material:
Carlo Lacagnina, Ge Peng, Robert Downs, Chris Schubert, Andrea Bertino, Sarah Stryeck, Oliver Biehlmaier
FAIR, CARE, TRUST - Adoption, Implementation, and Deployment
Training, Stewardship, and Data Management Planning