Skills4EOSC Skills for the European Open Science Commons: Creating a Training Ecosystem for Open and FAIR Science

Forskningsprojekt, 2022 – 2025

Skills4EOSC brings together leading experiences of national, regional, institutional and thematic Open Science (OS) and Data Competence Centres from 18 European countries with the goal of unifying the current training landscape into a common and trusted pan-European ecosystem, in order to accelerate the upskilling of European researchers and data professionals in the field of FAIR and Open Data, intensive-data science and Scientific Data Management.
Competence Centres (CC) are seen as centres of gravity of OS and EOSC activities in their countries. These entities can either be established national initiatives (as is the case of ICDI in Italy) or initiatives under establishment (e.g. Austria, Greece and the Nordic countries) or organizations which have the leading or mandated contribution to the OS activities nationally. CCs pool the expertise available within research institutions, universities and thematic and cross-discipline research infrastructures. They offer training and support, empowerment, lifelong learning, professionalization and resources to a variety of stakeholders, including not only researchers and data stewards, but also funders, decision makers, civil servants, and industry.
Thanks to their position at the heart of the above described multi-stakeholder landscape, the CCs represented by the Skills4EOSC partners play a pivotal role in national plans for Open Science and in the interaction with scientific communities. They also have close access to policy makers and the related funding streams. The Skills4EOSC project will leverage this reference role to establish a pan-European network of CCs on OS and data, coordinating
the work done at the national level to upskill professionals in this field.
The Skills4EOSC CC network will drive the co-creation of harmonised trainer accreditation pathways, academic and professional curricula and skills quality assurance, recognition frameworks, and learning material creation methodologies.