The OpenCitations Data Model

Open Access
Authors
  • B. Ghavimi
  • A. Lauscher
  • P. Mayr
  • M. Romanello
  • P. Zumstein
Publication date 2020
Host editors
  • J.Z. Pan
  • V. Tamma
  • C. d’Amato
  • K. Janowicz
  • B. Fu
  • A. Polleres
  • O. Seneviratne
  • L. Kagal
Book title The Semantic Web – ISWC 2020
Book subtitle 19th International Semantic Web Conference Athens, Greece, November 2–6, 2020 : Proceedings
ISBN
  • 9783030624651
ISBN (electronic)
  • 9783030624668
Series Lecture Notes in Computer Science
Event 19th International Semantic Web Conference, ISWC 2020
Volume | Issue number II
Pages (from-to) 447-463
Number of pages 17
Publisher Cham: Springer
Organisations
  • Faculty of Humanities (FGw) - Amsterdam Institute for Humanities Research (AIHR)
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract

A variety of schemas and ontologies are currently used for the machine-readable description of bibliographic entities and citations. This diversity, and the reuse of the same ontology terms with different nuances, generates inconsistencies in data. Adoption of a single data model would facilitate data integration tasks regardless of the data supplier or context application. In this paper we present the OpenCitations Data Model (OCDM), a generic data model for describing bibliographic entities and citations, developed using Semantic Web technologies. We also evaluate the effective reusability of OCDM according to ontology evaluation practices, mention existing users of OCDM, and discuss the use and impact of OCDM in the wider open science community.
Document type Conference contribution
Language English
Published at https://doi.org/10.1007/978-3-030-62466-8_28
Other links https://www.scopus.com/pages/publications/85096588595
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