Abstract
The Erasmus Programme is the biggest collaboration network consisting of European Higher Education Institutions (HEIs). The flows of students, teachers and staff form directed and weighted networks that connect institutions, regions and countries. Here, we present a linked and manually verified dataset of this multiplex, multipartite, multi-labelled, spatial network. We enriched the network with institutional socio-economic data from the European Tertiary Education Register (ETER) and the Global Research Identifier Database (GRID). We geocoded the headquarters of institutions and characterised the attractiveness and quality of their environments based on Points of Interest (POI) data. The linked datasets provide relevant information to grasp a more comprehensive understanding of the mobility patterns and attractiveness of the institutions.
Highlights
Background & SummaryThe Erasmus programme is the biggest collaboration network of European higher education institutions (HEIs)
The proposed integrated and validated network data can be used for profiling HEIs, studying socio-economic factors of mobility and measuring their attractivity based on the number of incoming students and lecturers
The understanding of the mechanisms, patterns and driving forces behind mobilities is a significant area of research as the development of integrated higher education is one of the focuses of the European Union[11,12] and most of the higher education ranking systems take into account the internationalization of HEIs
Summary
The Erasmus programme is the biggest collaboration network of European higher education institutions (HEIs). The dataset enriches the Erasmus mobility data with the connection between institutional variables of the European Tertiary Education Register (ETER) (https://www.eter-project.com) and the Global Research Identifier Database (GRID) (https://www.grid.ac) as well as the nearest points of interest (POI) (see Fig. 1). The proposed integrated and validated network data can be used for profiling HEIs, studying socio-economic factors of mobility and measuring their attractivity based on the number of incoming students and lecturers. The understanding of the mechanisms, patterns and driving forces behind mobilities is a significant area of research as the development of integrated higher education is one of the focuses of the European Union[11,12] and most of the higher education ranking systems take into account the internationalization of HEIs. Mobility networks can be considered as a multidimensional network where dimensions on edges originate from categorical variables, e.g. subject area, study level of students, participant type, of the mobility database. The time window of the network is too small to identify major changes in deeper socio-economic processes as the number of mobilities increases significantly every year, the analysis of this growing network might be an exciting topic of research
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