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 potential unbalances and to sustain changes in policy making, regulatory framework and educational approach requested by this rapid deployment of new data technologies, EU has shaped its recommendations which underline the importance of reskilling work force developing digital skills for industry and 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. The main objective of the ADSEE project is to deliver useful educational and training programme in data science (DS) through: development of educational modules, adaption of contents and methods according to envisaged needs of the target groups, creation of interactive didactic tools and production of guidelines and recommendations on innovative education approaches in DS. Special attention will be paid to data science in non-technical universities and its application in non-technical business, were 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 full-scale training case ("from business problem to business usage") and to fill the gap between increasing demand and 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 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 wider public, the main target groups are higher education institutions and HEIs employees, students, business/industry sector, institutions (ministries of labour, national employment agencies, employers' associations), Digital Innovation Hubs (DIH). ADSEE project addresses individuals with 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, are aware of its potential but still without an expertise to make decisions based on data science. In order to achieve the main objective, project partners have set up a set of activities that will result with five main intellectual outputs. - Report including a repository of existing DS training courses/study programmes and market needs in respect to relevant occupations, with a special attention to the non-technical sectors; - Interactive online repository as a focus point of the full learning materials, a tool for piloting and simulating use-cases in DS; - Transferable educational/training materials/modules covering wide range of different industries and cross-domain topics - At least four piloted and simulated use-cases - Guidelines for DS studies and for a 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 institutions specificities.
The main objective of the ADSEE project was to deliver useful educational and training programme in data science through development of educational modules, adaption of contents and methods according to envisaged needs of the target groups, creation of interactive didactic tools and production of guidelines and recommendations on innovative education approaches in data science. By implementing the project, we wanted to create innovative educational modules, specially paying our attention to prepare them in a way to be useful for learning about data-science in non-technical universities. The aim of this approach was to empower non-technical students and experts to apply data science approach and methods in non-technical business, particularly when it comes to data-driven decision making – necessary in many fields. Furthermore, our aim was to implement newly developed materials and modules into the project partners’ learning environments and therefore engage non-technical students with data science in order for them to acquire set of skills important for applying data science in their field of expertise, but also to popularize data science among students. Additionally, our aim was to show lecturers that ADSEE modules can be useful for implementing new teaching strategies and empower them to introduce data science into their teaching. Finally, through gathering important insights and evaluating project activities throughout the whole project lifetime, partners were trying to gather important information for creating guidelines with recommendations for future implementation of activities similar to ones implemented during project. This is how we strived to ensure sustainability, and future and international applicability of successful strategies designed during the project.
In 2016, 16 million people in Europe worked in data-related jobs and the overall value of the EU data economy reached almost 300 billion EUR – with respective increase expected in both categories according to “high grow” scenario. Therefore, the socio-economic aspect of data and data related industries proved to be crucial for the further development of the EU and its competitiveness capacities in the global economy. However, in 2016, a significant gap between total demand and supply of data workers was noticed, with a forecast to face a data skills gap corresponding to 769.000 unfilled positions by 2020. In order to mitigate potential unbalances on the labor market and to support adequate changes in educational approach, we identified the need for reskilling work force developing digital skills in the field of data science. In order to contribute to this change, we applied for this project to design ready-to-use materials, modules and strategies for HEIs which are often lagging behind in their role of developing and offering educational programmes and materials, providing students with skills which market demands. Especially, we identified that this need is very evident in non-technical sectors where domain-specific data skills are in high demand, but HEIs’ offer in relevant educational programmes and trainings is in many cases inadequate. Finally, ADSEE project was designed in order to deliver useful educational and training modules in data science, especially addressing non-technical HEIs and students.