Mapping STI ecosystems via Open Data: overcoming the limitations of conflicting taxonomies. A case study for Climate Change Research in Denmark

Bovenzi, Nicandro, Duran-Silva, Nicolau, Massucci, Francesco Alessandro, Multari, Francesco, Parra-Rojas, Cèsar, Pujol-Llatse, Josep

arXiv.org Artificial Intelligence 

Science, Technology and Innovation (STI) decision-makers often need to have a clear vision of what is researched and by whom to design effective policies. Such a vision is provided by effective and comprehensive mappings of the research activities carried out within their institutional boundaries. A major challenge to be faced in this context is the difficulty in accessing the relevant data and in combining information coming from different sources: indeed, traditionally, STI data has been confined within closed data sources and, when available, it is categorised with different taxonomies. Here, we present a proof-of-concept study of the use of Open Resources to map the research landscape on the Sustainable Development Goal (SDG) 13 - Climate Action, for an entire country, Denmark, and we map it on the 25 ERC panels.

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