The Open UniversitySkip to content

Integrating Knowledge Graphs for Comparing the Scientific Output of Academia and Industry

Angioni, Simone; Osborne, Francesco; Salatino, Angelo; Reforgiato Recupero, Diego and Motta, Enrico (2019). Integrating Knowledge Graphs for Comparing the Scientific Output of Academia and Industry. In: 18th International Semantic Web Conference (ISWC 2019): Posters & Demonstrations, Industry and Outrageous Ideas Tracks, 26-30 Oct 2019, Auckland, New Zeeland, CEUR WS, (In Press).

Full text available as:
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (168kB) | Preview
Google Scholar: Look up in Google Scholar


Analysing the relationship between academia and industry allows us to understand how the knowledge produced by the universities is being adopted and enriched by the industrial sector, and ultimately affects society through the release of relevant products and services. In this paper, we present a preliminary approach to assess and compare the research outputs of academia and industry. This solution integrates data from several knowledge graphs describing scientific articles (Microsoft Academics Graph), research topics (Computer Science Ontology), organizations (Global Research Identifier Database), and types of industry (DBpedia). We focus on the Semantic Web as exemplary field and report several insights regarding the different behaviours of academia and industry, and the types of industries most active in this field.

Item Type: Conference or Workshop Item
Keywords: Scholarly Data; Knowledge Graph; Science of Science; Ontology; Trend Analysis; Topic Detection; Taxonomy; Classifier; Academia; Industry
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 66174
Depositing User: Angelo Salatino
Date Deposited: 16 Aug 2019 08:22
Last Modified: 15 Nov 2019 05:07
Share this page:

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU