Home / FAIR Data Science and Professionalisation - WP7
This is in line with the FAIR data Expert Group recommendations to professionalise data science and stewardship and “to coordinate, systematise and accelerate the pedagogy and availability of training for data skills, data science and data stewardship”
The project addresses the development of a FAIR data competence framework. Activities include mapping data science programmes at universities and integrating FAIR data skills into them. Creating synergies with existing competence frameworks for data scientists, data stewards and other relevant professions, developing a FAIR data competence framework which can be integrated into those (e.g. by the EDISON or EOSCpilot projects) on different education levels, developing education and training material (e.g. model courses and curricula) for university programmes, and capacity building for universities to apply the material (e.g. for instance in doctoral education) are also envisaged.
Map the integration of FAIR data principles in data science and other curricula at universities and analyse the landscape of available FAIR data trainings in Europe.
Deliver a FAIR data competence framework for higher education and professionals to support the development of a FAIR data culture and the uptake of FAIR data principles in data science and other relevant disciplines.
Translate the competence framework into model curricula and university courses for different disciplines (e.g. data science) and professional profiles (e.g. data stewards)
Support embedding FAIR data education in university programmes and doctoral training through a series of workshops and knowledge-sharing activities.
University of Edinburgh - Digital Curation Centre (UEDIN)
European University Association (EUA)
The Science and Technology Facilities Council (STFC)
Trust-IT Services (Trust-IT)
University of Amsterdam (UvA)
Georg-August-Universität Göttingen Stiftung Öffentlichen Rechts (UGOE)
University of Minho (UMINHO)