Conveners
European Data Science Competence Framework
- Yuri Demchenko (University of Amsterdam)
Description
A series of stakeholder discussions have taken place over the last two years coordinated as part of the recently completed EDISON project. These events have helped to develop a consensus view on importance and complexity of data-related skills, competences and roles to support data dependent science and businesses. We propose to continue this conversation with a focus on capturing the commonalities and differences between the various research infrastructures and their related scientific domains.
Session aims
The session will bring together practitioners, educators and RI managers to discuss how the Data Science skills can be addressed in education, professional and workplace training, what framework models and approaches need to be developed to create sustainable critical competences and skills management for European research and industry.
The session will provide brief introduction on the EDISON Data Science Framework (EDSF) developed in the EU funded EDISON project and currently published as Release 2 under CC BY Open Source license, proposed roadmap and actions plan to create sustainable skills management and capacity building for EOSC and new Skills Agenda for Europe in general. This will be complemented by short/lightning talks from early implemented and adopter of data science education and training including universities, RIs, industry and governmental organisations. The second part of the session will host a panel of experts, practitioners and policy makers to discuss key actions to address Open Science and EOSC priorities in responding to demand of new skills critical for increasing efficiency and competitiveness of European research and industry.
EDISON Data Science Framework
The EDISON Data Science Framework (EDSF) includes four main components: Data Science Competence Framework (CF-DS), Data Science Body of Knowledge (DS-BoK), Data Science Model Curriculum (MC-DS), Data Science Professional profiles and occupations taxonomy (DSPP), and provide a conceptual framework and a model for building sustainable Data Science Educational Environment addressing needs of different stakeholders and professional groups and industries. The EDSF has been developed with wide participation and contribution from the European academia, research and industry and open for wide use and future development under CC BY Open Source license.
