9-12 May 2017
Europe/Rome timezone

EDISON Data Science Framework (EDSF): A foundation for sustainable skills management and capacity building on Data Science and Data Stewardship

Not scheduled


Yuri Demchenko (University of Amsterdam)


The education and training of Data Scientists currently lacks a commonly accepted, harmonized instructional model that reflects by design the whole lifecycle of data handling in modern, data driven research and the digital economy. This paper presents the EDISON Data Science Framework (EDSF) that is intended to create a foundation for the Data Science profession definition. The EDSF includes the following core components: Data Science Competence Framework (CF-DS), Data Science Body of Knowledge (DS-BoK), Data Science Model Curriculum (MC-DS), and Data Science Professional profiles (DSP profiles). The MC-DS is built based on CF-DS and DS-BoK, where Learning Outcomes are defined based on CF-DS competences and Learning Units are mapped to Knowledge Units in DS-BoK. In its own turn, Learning Units are defined based on the ACM Classification of Computer Science (CCS2012) and reflect typical courses naming used by universities in their current programmes. The paper provides example how the proposed EDSF can be used for designing effective Data Science curricula and reports the experience of implementing EDSF by the Champion Universities that cooperate with the EDISON project. The work of the EDISON project is specifically targeted to address issues of the data related skills and capacity building for European Open Science Cloud (EOSC) and European Digital Single Market (DSM), in particular targeting such issues as Data Stewardship, Research Data Management and research repeatability, and general data literacy.

Primary author

Yuri Demchenko (University of Amsterdam)


Mr Adam Belloum (University of Amsterdam) Steve Brewer (University of Southampton) Wouter Los (University of Amsterdam)

Presentation Materials

There are no materials yet.