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European Semantic Web Conference

ESWC 2023: The Semantic Web pp 436–453Cite as

An Upper Ontology for Modern Science Branches and Related Entities

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13870))

Abstract

Recent developments in the context of semantic technologies have given rise to ontologies for modelling scientific information in various fields of science. Over the past years, we have been engaged in the development of the Science Knowledge Graph Ontologies (SKGO), a set of ontologies for modelling research findings in various fields of science. This paper introduces the Modern Science Ontology (ModSci), an upper ontology for modelling relationships between modern science branches and related entities, including scientific discoveries, phenomena, prominent scientists, instruments, etc. ModSci provides a unifying framework for the various domain ontologies that make up the Science Knowledge Graph Ontology suite. Well-known ontology development guidelines and principles have been followed in the development and publication of the resource. We present several use cases and motivational scenarios to express the motivation behind developing the ontology and, therefore, its potential uses. We deem that within the next few years, a science knowledge graph is likely to become a crucial component for organizing and exploring scientific work.

S. Fathalla—The majority of the research presented in this work was carried out at the University of Bonn.

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Notes

  1. 1.

    https://msc2020.org/.

  2. 2.

    https://www.aeaweb.org/econlit/jelCodes.php.

  3. 3.

    https://www.catawiki.com/.

  4. 4.

    https://species.wikimedia.org/.

  5. 5.

    https://www.answers.com/.

  6. 6.

    https://ncatlab.org/.

  7. 7.

    https://en.wikipedia.org/wiki/Gene_Wiki.

  8. 8.

    https://www.snpedia.com/.

  9. 9.

    https://projects.tib.eu/orkg/.

  10. 10.

    https://nfdi4culture.de.

  11. 11.

    https://nfdi-matwerk.de/.

  12. 12.

    https://www.dfg.de/en/dfg_profile/statutory_bodies/review_boards/subject_areas/.

  13. 13.

    http://ontologydesignpatterns.org/wiki/Community:ListPatterns.

  14. 14.

    https://github.com/saidfathalla/Science-knowledge-graph-ontologies.

  15. 15.

    http://bioportal.bioontology.org/ontologies/MODSCI.

  16. 16.

    https://lov.linkeddata.es/dataset/lov/vocabs/modsci.

  17. 17.

    https://discuss.okfn.org/.

  18. 18.

    http://oops.linkeddata.es/.

  19. 19.

    https://w3id.org/widoco/bestPractices.

  20. 20.

    The final set of competency questions is available at the GitHub repository.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Bonn & Institute of Advanced Simulation - Materials Data Science and Informatics (IAS-9), Forschungszentrum Jülich, Jülich, Germany

    Said Fathalla

  2. Faculty of Science, University of Alexandria, Alexandria, Egypt

    Said Fathalla

  3. RWTH Aachen University, Germany & Fraunhofer FIT, Aachen, Germany

    Christoph Lange

  4. TIB Leibniz Information Centre for Science and Technology & L3S Research Center, University of Hannover, Hannover, Germany

    Sören Auer

Authors
  1. Said Fathalla
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  2. Christoph Lange
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  3. Sören Auer
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Corresponding author

Correspondence to Said Fathalla .

Editor information

Editors and Affiliations

  1. Universidade de Lisboa, Lisbon, Portugal

    Catia Pesquita

  2. University of London, London, UK

    Ernesto Jimenez-Ruiz

  3. Rensselaer Polytechnic Institute, Troy, MI, USA

    Jamie McCusker

  4. Universidade de Lisboa, Lisbon, Portugal

    Daniel Faria

  5. Fondazione Bruno Kessler, Povo, Trento, Italy

    Mauro Dragoni

  6. KU Leuven, Sint-Katelijne-Waver, Belgium

    Anastasia Dimou

  7. EURECOM, Biot, France

    Raphael Troncy

  8. University of Mannheim, Mannheim, Germany

    Sven Hertling

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Fathalla, S., Lange, C., Auer, S. (2023). An Upper Ontology for Modern Science Branches and Related Entities. In: Pesquita, C., et al. The Semantic Web. ESWC 2023. Lecture Notes in Computer Science, vol 13870. Springer, Cham. https://doi.org/10.1007/978-3-031-33455-9_26

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  • DOI: https://doi.org/10.1007/978-3-031-33455-9_26

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