Analysing the requirements for an Open Research Knowledge Graph: use cases, quality requirements, and construction strategies

• Published in: International journal on digital libraries Vol. 23; no. 1; pp. 33 - 55
• Main Authors: Brack, Arthur, Hoppe, Anett, Stocker, Markus, Auer, Sören, Ewerth, Ralph
• Format: Journal Article
• Language: English
• Published: Berlin, Heidelberg Springer 01.03.2022; Springer Berlin Heidelberg; Springer Nature B.V
• Subjects: Citations; Computer Science; Database Management; Datasets; Design science research; Digital libraries; Digital Object Identifier; Documents; Information Systems and Communication Service; Keywords; Knowledge representation; Literature reviews; Machine learning; Metadata; Ontology; R&D; Reproducibility; Requirements analysis; Research & development; Research knowledge graph; Scholarly communication; Science; Search engines; Semantics; State-of-the-art reviews; Research knowledge graph; Requirements analysis; Scholarly communication; Design science research
• ISSN: 1432-1300; 1432-5012; 1432-1300
• DOI: 10.1007/s00799-021-00306-x

Current science communication has a number of drawbacks and bottlenecks which have been subject of discussion lately: Among others, the rising number of published articles makes it nearly impossible to get a full overview of the state of the art in a certain field, or reproducibility is hampered by fixed-length, document-based publications which normally cannot cover all details of a research work. Recently, several initiatives have proposed knowledge graphs (KG) for organising scientific information as a solution to many of the current issues. The focus of these proposals is, however, usually restricted to very specific use cases. In this paper, we aim to transcend this limited perspective and present a comprehensive analysis of requirements for an Open Research Knowledge Graph (ORKG) by (a) collecting and reviewing daily core tasks of a scientist, (b) establishing their consequential requirements for a KG-based system, (c) identifying overlaps and specificities, and their coverage in current solutions. As a result, we map necessary and desirable requirements for successful KG-based science communication, derive implications, and outline possible solutions.