Presentation Open Access
Huiku, Leena; Grassi, Fabio; Hyrkkänen, Anna-Kaisa; Pasanen, Irma; Sonkkila, Tuija
This study presents two different approaches to address topics on one hand related to sustainability defined by the UN Sustainable Development Goals (SDGs) and on the other hand topics related to the Societal Grand Challenges (SGCs) and Key Enabling Technologies (KETs) defined by EU Horizon2020.
The commercial services Elsevier and Times Higher Education have developed tools to monitor and address topics related to SDGs. EU funded RISIS-KNOWMAK (Knowledge in the ‘making’) tool is on the visualisation and investigation of the production of knowledge in the European Research Area, with a particular focus on knowledge related to SGCs and KETs. The KNOWMAK ontology provides concepts around SGCs and KETs.
Our SDG study utilizes the search strings by Elsevier Scopus database that are freely available and that are used in the Times Higher Education Impact Ranking. The search strings are converted to Web of Science database and the comparison between the Web of Science and our own database has been conducted in this investigation.
The SGC and KET analyses are based on the publication, project and patent datasets provided us by RISIS-KNOWMAK project in addition to our own publication materials. The KNOWMAK ontology has been utilized in the creation of the search strings that our bibliometric analyses are based on. Two specific SGC and KET topics based on the ontology are chosen for deeper analyses. The similar analysis is conducted based on SDGs terminology. Comparison with results from different approaches has been carried out.
The results showcase that the terminology and ontology-based analyses provide valuable information for research institutes to identify the key areas and actors on these topics. This in turn may open new possibilities for collaboration between the actors. The search strings should be built carefully because not only the semantics but the syntax is important to the results achieved. The differences between the data sources are shown in this study.
Huiku et al Terminology-based approach_NWB2020_presentation.pdf