AIDA: A knowledge graph about research dynamics in academia and industry
Author(s) -
Simone Angioni,
Angelo A. Salatino,
Francesco Osborne,
Diego Reforgiato Recupero,
Enrico Motta
Publication year - 2021
Publication title -
quantitative science studies
Language(s) - English
Resource type - Journals
ISSN - 2641-3337
DOI - 10.1162/qss_a_00162
Subject(s) - computer science , identifier , ontology , pipeline (software) , data science , graph , theoretical computer science , philosophy , epistemology , programming language
Academia and industry share a complex, multifaceted, and symbiotic relationship. Analyzing the knowledge flow between them, understanding which directions have the biggest potential, and discovering the best strategies to harmonize their efforts is a critical task for several stakeholders. Research publications and patents are an ideal medium to analyze this space, but current data sets of scholarly data cannot be used for such a purpose because they lack a high-quality characterization of the relevant research topics and industrial sectors. In this paper, we introduce the Academia/Industry DynAmics (AIDA) Knowledge Graph, which describes 21 million publications and 8 million patents according to the research topics drawn from the Computer Science Ontology. 5.1 million publications and 5.6 million patents are further characterized according to the type of the author’s affiliations and 66 industrial sectors from the proposed Industrial Sectors Ontology (INDUSO). AIDA was generated by an automatic pipeline that integrates data from Microsoft Academic Graph, Dimensions, DBpedia, the Computer Science Ontology, and the Global Research Identifier Database. It is publicly available under CC BY 4.0 and can be downloaded as a dump or queried via a triplestore. We evaluated the different parts of the generation pipeline on a manually crafted gold standard yielding competitive results.
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