Research publishing companies need to constantly monitor and compare scientific journals and conferences in order to inform critical business and editorial decisions. Semantic Web and Knowledge Graph technologies are natural solutions since they allow these companies to integrate, represent, and analyse a large quantity of information from heterogeneous sources. In this paper, we present the AIDA Dashboard 2.0, an innovative system developed in collaboration with Springer Nature to analyse and compare scientific venues, now also available to the public. This tool builds on a knowledge graph which includes over 1.5B RDF triples and was produced by integrating information about 25M research articles from Microsoft Academic Graph, Dimensions, DBpedia, GRID, CSO, and INDUSO. It can produce sophisticated analytics and rankings that are not available in alternative systems. We discuss the advantages of this solution for the Springer Nature editorial process and present a user study involving 5 editors and 5 researchers, which yielded excellent results in terms of quality of the analytics and usability.

Leveraging Knowledge Graph Technologies to Assess Journals and Conferences at Springer Nature

Reforgiato Recupero Diego
;
2022-01-01

Abstract

Research publishing companies need to constantly monitor and compare scientific journals and conferences in order to inform critical business and editorial decisions. Semantic Web and Knowledge Graph technologies are natural solutions since they allow these companies to integrate, represent, and analyse a large quantity of information from heterogeneous sources. In this paper, we present the AIDA Dashboard 2.0, an innovative system developed in collaboration with Springer Nature to analyse and compare scientific venues, now also available to the public. This tool builds on a knowledge graph which includes over 1.5B RDF triples and was produced by integrating information about 25M research articles from Microsoft Academic Graph, Dimensions, DBpedia, GRID, CSO, and INDUSO. It can produce sophisticated analytics and rankings that are not available in alternative systems. We discuss the advantages of this solution for the Springer Nature editorial process and present a user study involving 5 editors and 5 researchers, which yielded excellent results in terms of quality of the analytics and usability.
978-3-031-19432-0
978-3-031-19433-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/349908
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