DGTES database 2022

The DGTES digital ecosystem database is generated form the application of the Techno-Economic ecosystem (TES) methodological approach to the study of the digital ecosystem from a multidimensional perspective, providing an overview of the worldwide landscape of the digital ecosystem. The main elements of the DGTES digital ecosystem database are players and activities. The unit of the analysis is the economic agent, or player, that can be a company, university, research institution or governmental authority. The player is expected to have an active role in the digital ecosystem, with the capability to influence its economic development and future evolution. The focus is thus set on the organisations, and not on individuals, namely the applicant organisation owning the invention in the case of patents, authors’ affiliation in conference proceedings, companies, governmental entities, etc. The DGTES dataset targets both industrial and R&D activities: economic activities of interest for the analysis of the DGTES include participation in R&D processes (research, in the sense of publication of scientific articles or/and participation in international conferences; innovative developments, such as filing patents; participation in EU research funds, such as Horizon 2020 or FP7), general economic processes (industrial production, trade), firms funding (venture capital funds). The results are provided aggregated by country of location of the institutions concerned. The DGTES database reflects the complex structure of the digital ecosystem, as it contains detailed information about the participation of each player in the detected activities and about their features, such as information on geographical location and date, over the period 2009-2022. To obtain this database, DGTES uses a comprehensive dictionary of keywords built for the specific domain of digital technologies to search through different sources of factual data, and to identify players, activities and their networks of connections and interlinkages.

Elisa Calza; Michele Carenini; Giuditta De Prato (2022): DGTES database 2022. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/1e0c26f9-09ea-4cb3-9b4c-ff97e165bce7