The socio-economic aspect of data and data related industries are crucial for the further development of the European Union and its competitiveness capacities in the global economy. Every day 2.5 quintillion bytes of data are created by different sources while 6.16 million people in Europe worked in data-related jobs in 2016, with a perspective to see the number of workers increasing up to 10.43 million by 2020. On the other side, the overall value of the EU data economy reached almost 300 billion EUR in 2016 and according to the “high grow” scenario the value will reach 739 billion by 2020, with an overall impact of 4% in the EU GDP.

However, there is an existing gap between total demand and supply of data workers of 420.000 in EU in 2016, with a forecast to face a data skills gap corresponding to 769.000 unfilled positions by 2020. In order to mitigate the potential inbalances that fast changes due to the rapid deployment in new data technologies may introduce to policy making and regulatory and educational platforms, the EU has shaped its recommendations which underline the importance of reskilling a work force with developed industrial digital skills. The EU has also launched its agendas to boost human capital, employability and competitiveness by modernising education and training curricula/study programs.

Facing stated challenges, universities and other HEIs are often lagging behind in their role of developing and offering educational programmes and materials, providing students with skills which market demands, thus indirectly creating a consistent gap between demand and supply of qualified workers. This is even more evident in non-technical sectors where domain-specific data skills are in high demand.

Our aims and objectives:

The main objective of the ADSEE project is to deliver useful educational and training programs in data science through the following: the development of educational modules; the adaption of contents and methods according to the envisioned needs of target groups; the creation of interactive didactic tools and the production of guidelines and recommendations for the innovative educational approaches in DS. Special attention will be paid to data science in non-technical universities and its application in non-technical business, where previous knowledge in this area is not mandatory.

The innovativeness of the project lies in the modular approach allowing tailor-made courses development, according to the participants’ specific prior knowledge and competences (or in absence of that knowledge/competences) and in a fully functioning online piloting repository which will contribute to the development of participants’ new skills and experiences by delivering material in a full-scale training case (“from business problem to business usage”) and to fill the gap between the increasing demand and the limited supply of business sector for practical training methods and approaches.
Thanks to a modular approach used to develop educational and training material, all modules will be transferable and applicable in any study program since they will be structured in a flexible end-to-end business case avoiding a pure data scientific approach.

The partnership comprises 5 partners : Algebra University College Croatia; University of Amsterdam, The Netherlands; German National Library and Leibniz Information Centre for Science and Technology, Germany; Faculty of Information Studies, Slovenia; Arctur ltd, Slovenia.

Whereas the project will contribute to the popularisation of Data Science among the wider public, the main target groups are higher education institutions and HEIs employees, students, the business/industry sector, institutions (ministries of labour, national employment agencies, employers’ associations), and Digital Innovation Hubs (DIH). ADSEE project addresses individuals with an in-depth knowledge about data science, those who are attending technical universities or are working in DS related sectors and individuals who know DS exists, and are aware of its potential but still lack the expertise to make decisions based on data science.

Our intellectual outputs:

In order to achieve the main objective, project partners have set up a set of activities that will result in five main intellectual outputs:

  • A report including a repository of existing DS training courses/study programmes and market needs with respect to relevant occupations, with special attention paid to the non-technical sectors
  • An interactive online repository which focusses on the full scope of learning materials, and serves as a tool for piloting and simulating use-cases in DS
  • Transferable educational/training materials/modules which cover a wide range of different industries and cross-domain topics
  • At least four piloted and simulated use-cases
  • Guidelines for DS studies and for non-DS studies (studies that have implemented DS as horizontal element in curricula
    and studies that haven’t implemented DS in curricula at all) including tailoring recommendations in relation to specific institutional specificities.

Project work packages:

The project consists of several Work Packages:

Project Start Date:

  • 04-11-2019

Project End Date:

  • 03-04-2022

Project Total Duration:

  • 29 months

Total Project Budget:

  • 261.517,00 EUR