RESUMEN
The EUPRO database enables the analysis of participation patterns of organisations in and across different European R&D funding initiatives and the investigation of resulting collaborative R&D network structures and dynamics. The perimeter of EUPRO is currently more than 600,000 R&D projects funded by European (EU, transnational or national) research funding organisations, comprising systematic information about contents of the R&D projects, their participating organizations (including organisation type and location), and a number of additional characteristics (e.g. underlying policy instrument and programme). This scientific data descriptor serves as illustrative information source for users, both from science as well as from policy. It discusses the conceptual background and derives respective analytical opportunities for different actual, highly relevant debates in innovation studies and related fields. Moreover, the data collection process is described in a compact manner, as well as how the collected data are harmonized and aggregated into a suitable data model for analytical purposes. Finally, we put forward issues of technical validation, data quality and enrichment, and usage notes on how to access EUPRO.
RESUMEN
The European Tertiary Education Register (ETER) is the reference dataset on European Higher Education Institutions (HEIs). ETER provides data on nearly 3,500 HEIs in about 40 European countries, including descriptive information, geographical information, students and graduates (with various breakdowns), revenues and expenditures, personnel, and research activities; as of March 2023, data cover the years from 2011-2020. ETER complies with OECD-UNESCO-EUROSTAT standards for educational statistics; most data are collected from National Statistical Authorities (NSAs) or ministries of participating countries and are subject to extensive checks and harmonization. The development of ETER has been funded by the European Commission and is part of the current efforts to establish a European Higher Education Sector Observatory; it is closely connected to the establishment of a broader data infrastructure in the field of science and innovation studies (RISIS). The ETER dataset is widely used in the scholarly literature on higher education and science policy, as well as for policy reports and analyses.
RESUMEN
The focus of this study is on the geography of robotics Research and Development (R&D) activities. The objectives are, first, to identify hotspots in robotics R&D worldwide, and second, to characterise structures and dynamics of global robotics R&D collaboration networks through detailed geographical lenses of global urban areas. We use patents as marker for R&D activities, and accordingly focus on technologically oriented R&D, drawing on information from patents applied for between 2002 and 2016. We employ an appropriate search strategy to identify relevant robotics patents based on detailed levels of the Cooperative Patent Classification (CPC) and assign patents to more than 900 global urban areas based on the inventor addresses. The co-patent networks are examined from a Social Network Analysis (SNA) perspective by means of robotics co-patents, contributing to a global network where urban areas are the nodes inter-linked by joint inventive activities recorded in robotics patents. Global SNA measures illustrate structures and dynamics of the network as a whole, while local measures indicate the specific positioning and roles of urban areas in the network. The results are original in characterising the global spatial emergence of this generic new industry, highlighting prominent urban hotspots in terms of specialisation in robotics R&D, pointing to a global shift reflected by the increasing role of emerging economies, in particular China. The global robotics R&D has grown significantly both in total patenting and also in terms of R&D collaboration activities between urban areas. Also, for the networks, growth is not equally distributed, but is rather characterised by significant spatial shifts, both in terms of cities declining or climbing up the specialisation ranking, but even more in terms of the spatial network structure.
