Periodic Reporting for period 1 - LearnData (Collective Learning Data Lab)
Période du rapport: 2023-01-01 au 2024-03-31
Corvinus University of Budapest (CUB) is the number one university in Hungary in economic and business studies that offers degrees – among many others – in Applied Economics, Communications and Media Studies, and International Relations, both in Hungarian and in English. Despite its ability to attract the most talented students within the country, CUB does not stand out in international comparison. The overarching aim of the ERA Chair project is to increase research and teaching excellence in Applied Data Science oriented for Economics, Business Studies, Social Sciences, and Economic Geography that would contribute to CUB’s international competitiveness.
The ongoing Renewal Program of the University aims at international research excellence and experiential teaching that provides full support for the ERA Chair lab and helps its embedding into the university fabric.
Data fuels the digital economy. This demands training new generations of experts on how data is collected, stored, processed, and analysed. CUB is working to become a leading business and economics university in Central and Eastern Europe by combining data science skills with expert knowledge in business and economics. The support of the ERA Chair Program will reinforce institutional reforms at CUB designed to transform it into a hub of research and teaching excellence in applied data science, expanding the international attractiveness of CUB through cutting-edge training programs and innovative industry collaborations. We will establish the new Collective Learning Data Lab (CLDL, which is also referred to as Center for Collective Learning or CCL) with the leadership of Professor César Hidalgo, a worldclass researcher in data science, economic geography, and network science. By leveraging synergies with outstanding research groups at CUB, the Collective Learning Data Lab is projected to grow into a leading Center for Data and Network Science. This will create an environment for the university to learn key methods and publish in top interdisciplinary, economics, business, and social science journals. The Lab will be a flagship project involving students in experiential data-driven work. Lab members will engage in advising PhD programs and in developing BA specializations and Master programs in social- and business-oriented data science. The Lab will widen CUB’s industry collaborations with data-oriented companies and public policy use cases. Building on Budapest’s strong tradition in network science, CLDL will impact Hungary and Central and Eastern Europe by equipping society with the skills needed to undertake new challenges
The ongoing Renewal Program of the University aims at international research excellence and experiential teaching that provides full support for the ERA Chair lab and helps its embedding into the university fabric.
Data fuels the digital economy. This demands training new generations of experts on how data is collected, stored, processed, and analysed. CUB is working to become a leading business and economics university in Central and Eastern Europe by combining data science skills with expert knowledge in business and economics. The support of the ERA Chair Program will reinforce institutional reforms at CUB designed to transform it into a hub of research and teaching excellence in applied data science, expanding the international attractiveness of CUB through cutting-edge training programs and innovative industry collaborations. We will establish the new Collective Learning Data Lab (CLDL, which is also referred to as Center for Collective Learning or CCL) with the leadership of Professor César Hidalgo, a worldclass researcher in data science, economic geography, and network science. By leveraging synergies with outstanding research groups at CUB, the Collective Learning Data Lab is projected to grow into a leading Center for Data and Network Science. This will create an environment for the university to learn key methods and publish in top interdisciplinary, economics, business, and social science journals. The Lab will be a flagship project involving students in experiential data-driven work. Lab members will engage in advising PhD programs and in developing BA specializations and Master programs in social- and business-oriented data science. The Lab will widen CUB’s industry collaborations with data-oriented companies and public policy use cases. Building on Budapest’s strong tradition in network science, CLDL will impact Hungary and Central and Eastern Europe by equipping society with the skills needed to undertake new challenges
By the end of the first reporting period CUB successfully established the Center for Collective Learning data lab and launched it to the wider public as well. As the team was set up, they were immediately actively conducting research and their works (6 papers) were published in Scrimago Q1 journals. The team had as well launched a data visualisation project. It consist of a platform, that is data visualisation tool that enables users (both scientific and non-scientific audiences) to learn more about the complex interconnectedness of univerisites world-wide. It provides insight into issues that a simple ranking system may not be able to address. The platform offers a new perspective on how universities influence and interact with their specific geographical and topical areas (for more information, please visit rankless.org).
Alongside the scientific advances carried out by the team, with the active collaboration of the ERA Chair holder, the Assistant professors, and the Executive Director, the detailed plan of a new MSc programme plan has been submitted. Following the approval process at the University, the programme plan will be submitted for accreditation to the Ministry of Culture and Innovation. To set the foundation of the sustainability of the lab after the project lifecycle has come to end, scientific collaborations have advanced with industry partners and academia both within CUB and in the region.
Alongside the scientific advances carried out by the team, with the active collaboration of the ERA Chair holder, the Assistant professors, and the Executive Director, the detailed plan of a new MSc programme plan has been submitted. Following the approval process at the University, the programme plan will be submitted for accreditation to the Ministry of Culture and Innovation. To set the foundation of the sustainability of the lab after the project lifecycle has come to end, scientific collaborations have advanced with industry partners and academia both within CUB and in the region.
Out of the 10 impact areas anticipated, the first three:
• Scientific excellence of CUB in data science,
• Attractiveness of CUB for internationally excellent researchers
• Creation of a permanent excellent group and its spillovers to other units
are completed. Success of these areas can be seen in the quality of papers submitted and accepted (in Scrimago Q1 journals), in the fact that candidates were applying for the different open position from all around the world, and last but not least, in the highly qualified researchers who are working in the Lab.
All other areas of impact have started, but are not yet finished.
• Scientific excellence of CUB in data science,
• Attractiveness of CUB for internationally excellent researchers
• Creation of a permanent excellent group and its spillovers to other units
are completed. Success of these areas can be seen in the quality of papers submitted and accepted (in Scrimago Q1 journals), in the fact that candidates were applying for the different open position from all around the world, and last but not least, in the highly qualified researchers who are working in the Lab.
All other areas of impact have started, but are not yet finished.