Academia and industry are constantly engaged in a joint effort for producing scientific knowledge that will shape the society of the future. Analysing the knowledge flow between them and understanding how they influence each other is a critical task for researchers, governments, funding bodies, investors, and companies. However, current corpora are unfit to support large-scale analysis of the knowledge flow between academia and industry since they lack of a good characterization of research topics and industrial sectors. In this short paper, we introduce the Academia/Industry DynAmics (AIDA) Knowledge Graph, which characterizes 14M papers and 8M patents according to the research topics drawn from the Computer Science Ontology. 4M papers and 5M patents are also classified according to the type of the author’s affiliations (academy, industry, or collaborative) and 66 industrial sectors (e.g., automotive, financial, energy, electronics) obtained from DBpedia. AIDA was generated by an automatic pipeline that integrates several knowledge graphs and bibliographic corpora, including Microsoft Academic Graph, Dimensions, English DBpedia, the Computer Science Ontology, and the Global Research Identifier Database.

Angioni, S., Salatino, A., Osborne, F., Recupero, D., & Motta, E. (2020). Integrating knowledge graphs for analysing academia and industry dynamics. In ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium (pp.219-225). Springer [10.1007/978-3-030-55814-7_18].

Integrating knowledge graphs for analysing academia and industry dynamics

Osborne F;
2020

Abstract

Academia and industry are constantly engaged in a joint effort for producing scientific knowledge that will shape the society of the future. Analysing the knowledge flow between them and understanding how they influence each other is a critical task for researchers, governments, funding bodies, investors, and companies. However, current corpora are unfit to support large-scale analysis of the knowledge flow between academia and industry since they lack of a good characterization of research topics and industrial sectors. In this short paper, we introduce the Academia/Industry DynAmics (AIDA) Knowledge Graph, which characterizes 14M papers and 8M patents according to the research topics drawn from the Computer Science Ontology. 4M papers and 5M patents are also classified according to the type of the author’s affiliations (academy, industry, or collaborative) and 66 industrial sectors (e.g., automotive, financial, energy, electronics) obtained from DBpedia. AIDA was generated by an automatic pipeline that integrates several knowledge graphs and bibliographic corpora, including Microsoft Academic Graph, Dimensions, English DBpedia, the Computer Science Ontology, and the Global Research Identifier Database.
Si
paper
Scientifica
Bibliographic data; Knowledge graph; Research dynamics; Scholarly data; Scholarly ontologies; Topic detection;
English
24th East-European Conference on Advances in Databases and Information Systems, ADBIS 2020, the 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, and the 16th Workshop on Business Intelligence and Big Data, EDA 2020 - 25 August 2020 through 27 August 2020
978-303055813-0
https://link.springer.com/chapter/10.1007/978-3-030-55814-7_18
Angioni, S., Salatino, A., Osborne, F., Recupero, D., & Motta, E. (2020). Integrating knowledge graphs for analysing academia and industry dynamics. In ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium (pp.219-225). Springer [10.1007/978-3-030-55814-7_18].
Angioni, S; Salatino, A; Osborne, F; Recupero, D; Motta, E
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10281/381217
Citazioni
  • Scopus 10
  • ???jsp.display-item.citation.isi??? ND
Social impact