Mapping STI Ecosystems via Open Data: Overcoming the Limitations of Conflicting Taxonomies. A Case Study for Climate Change Research in Denmark

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Article , Conference object , Other literature type , Preprint 01 Jan 2022Embargo end date: 01 Jan 2022 English Publisher:Springer International PublishingFunded by:EC | INODE

Authors: Nicandro Bovenzi; Nicolau Duran-Silva; Francesco Alessandro Massucci; Francesco Multari; César Parra-Rojas; Josep Pujol-Llatse;

doi: 10.1007/978-3-031-16802-4_52 , 10.48550/arxiv.2209.08920 , 10.5281/zenodo.7096519 , 10.5281/zenodo.7096520

arXiv: 2209.08920

Mapping STI Ecosystems via Open Data: Overcoming the Limitations of Conflicting Taxonomies. A Case Study for Climate Change Research in Denmark

- Summary
- Subjects
- Metrics

Abstract

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.

International Conference on Theory and Practice of Digital Libraries (TPDL) 2022

Related Organizations

SIRIS ACADEMIC SL
Spain
SIRIS Academic SL
Spain

Keywords

Science mapping, FOS: Computer and information sciences, Computer Science - Computation and Language, Text mining, Sustainable Development Goals, Computer Science - Digital Libraries, Deep learning, Open data repositories, Digital Libraries (cs.DL), Computation and Language (cs.CL)

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average