Mapping Climate Change Research via Open Repositories & AI: advantages and limitations for an evidence-based R&D policy-making

TL;DR

This paper explores the use of open access research data and AI to map Climate Action research in Denmark, highlighting benefits for policy-making and discussing challenges related to data interoperability.

Contribution

It evaluates the effectiveness and limitations of combining multiple open STI data sources for comprehensive climate research mapping.

Findings

Open data sources can effectively identify climate research assets.

Interoperability issues limit comprehensive ecosystem mapping.

AI techniques can enhance knowledge discovery in STI data.

Abstract

In the last few years, several initiatives have been starting to offer access to research outputs data and metadata in an open fashion. The platforms developed by those initiatives are opening up scientific production to the wider public and they can be an invaluable asset for evidence-based policy-making in Science, Technology and Innovation (STI). These resources can indeed facilitate knowledge discovery and help identify available R&D assets and relevant actors within specific research niches of interest. Ideally, to gain a comprehensive view of entire STI ecosystems, the information provided by each of these resources should be combined and analysed accordingly. To ensure so, at least a certain degree of interoperability should be guaranteed across data sources, so that data could be better aggregated and complemented and that evidence provided towards policy-making is more complete and reliable. Here, we study whether this is the case for the case of mapping Climate Action research in the whole Denmark STI ecosystem, by using 4 popular open access STI data sources, namely OpenAire, Open Alex, CORDIS and Kohesio.