Description
The productivity of research data within a trustworthy and reliable process chain requires a precise statement on FAIRness and data quality management for the targeted support of digital research objects, infrastructures, tools and services.
Both fundamentals, FAIR and data quality in research data management, face specifics, e.g., for data lifecycle, provenance, and the re-use of data across thematic domains. Do we have any mechanisms to provide low-barrier opportunities for implementing indicators from a funding perspective? What are the incentives and benefits as the value in governance, community development of standards, and metrics?
In this participative discussion, we would like to provide insights into the potential benefits and individual incentives that infrastructures like the NFDI consortia, policymakers, and funding agencies or publishers can offer to individual research activities in promoting the development of FAIR Metrics and data quality considering rapid technological developments and advanced requirements.
Opening by Chris Schubert, TU Wien
Introduction by Kathrin Winkler, European Commission, DG R&I
