ESFRI Science Clusters Position Statement on Expectations and Long-Term Commitment in Open Science

THE SCIENCE CLUSTERS are EU collaborative projects that were launched in 2019 to link ESFRI and other world-class Research Infrastructures (RIs) to the European Open Science Cloud (EOSC). The main impacts of the Science Clusters’ work programme concern: the improved access of researchers to data, tools and resources, leading to new insights and innovation for data-driven science both within and beyond the context of the domains in which the clusters are rooted; the creation of a cross-border open innovation environment for FAIR (Findable, Accessible, Interoperable and Reusable) data management for economies of scale, to develop synergies and rise the efficiency and productivity of researchers through open-science standards and thematic services; the enhanced co-developments to foster the cross-domain interoperability central to the EOSC goal. The Science Clusters are an integral part of EOSC. Their services and outcomes are now forming the core of the emerging EOSC fabric. As important partners of EOSC, Science Clusters contribute to its development and its implementation process. Importantly, the Science Clusters form a natural collaboration between the ESFRI RIs’ management boards partners in the clusters. As EOSC matures and begins delivering data and services for European research, a discussion is needed to stimulate the Open Science practices, cross-domain interoperability and long-term coordination of the scientific communities covered by the five Science Clusters. This position paper contributes formally to explain the urgent need of EC to support a longer-term role of the five Science Clusters to provide content to the EOSC, to enhance researchers’ involvement in Open Science and to suggest potential cooperative pathways in the Horizon-Europe framework and along with the EOSC Association roadmap. This paper is aimed at highlighting: Expectations of the clusters and the concerned research communities, pointing out a common structured vision and a series of suggestions for the future. A more detailed analysis from each cluster, that is provided for completeness