edsa project full details
Timeline:02 Feb 2015 - 31 Jan 2018
European Data Science Academy
Data explosion on the web, fuelled by social networking, micro-blogging, as well as crowdsourcing, has led to the Big Data phenomenon. This is characterized by increasing volumes of structured, semi-structured and unstructured data, originating from sources that generate them at an increasing rate. This wealth of data provides numerous new analytic and business intelligence opportunities to various industry sectors. Therefore, more and more industry sectors are in need of innovative data management services, creating a demand for Data Scientists possessing skills and detailed knowledge in this area. Ensuring the availability of such expertise will prove crucial if businesses are to reap the full benefits of these advanced data management technologies, and the know-how accumulated over the past years by researchers, technology enthusiasts and early adopters.
The European Data Science Academy (EDSA) will establish a virtuous learning production cycle whereby we: a) analyse the required sector specific skillsets for data analysts across the main industrial sectors in Europe; b) develop modular and adaptable data science curricula to meet these needs; and c) deliver training supported by multiplatform and multilingual learning resources based on our curricula. The curricula and learning resources will be continuously evaluated by pedagogical and data science experts during both development and deployment.
25 Jan 2018
30 Nov 2017
02 Oct 2017
14 Mar 2017
10 Feb 2017
Dadzie, A., Sibarani, E., Novalija, I. and Scerri, S. (2017) Structuring visual exploratory analysis of skill demand, Journal of Web Semantics
Mikroyannidis, A., Domingue, J., Phethean, C., Beeston, G. and Simperl, E. (2017) Designing and Delivering a Curriculum for Data Science Education across Europe, 20th International Conference on Interactive Collaborative Learning (ICL 2017), Budapest, Hungary, pp. 243-253, Springer
Mikroyannidis, A., Domingue, J., Phethean, C., Beeston, G. and Simperl, E. (2017) The European Data Science Academy: Bridging the Data Science Skills Gap with Open Courseware, Open Education Global conference, Cape Town, South Africa
Weller, K., Dadzie, A. and Radovanović, D. (2016) Making Sense of Microposts (#Microposts2016) Social Sciences Track, Workshop: Making Sense of Microposts: Big things come in small packages (#Microposts2016) at 25th International World Wide Web Conference (WWW 2016), Montréal, Canada, pp. 29-32
Dadzie, A. and Domingue, J. (2015) Visual Exploration of Formal Requirements for Data Science Demand Analysis, Workshop: Visualizations and User Interfaces for Ontologies and Linked Data (VOILA 2015) at ISWC 2015, Bethlehem, Pennsylvania, USA