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Ontology Design for Pharmaceutical Research Outcomes

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Digital Libraries for Open Knowledge (TPDL 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12246))

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Abstract

The network of scholarly publishing involves generating and exchanging ideas, certifying research, publishing in order to disseminate findings, and preserving outputs. Despite enormous efforts in providing support for each of those steps in scholarly communication, identifying knowledge fragments is still a big challenge. This is due to the heterogeneous nature of the scholarly data and the current paradigm of distribution by publishing (mostly document-based) over journal articles, numerous repositories, and libraries. Therefore, transforming this paradigm to knowledge-based representation is expected to reform the knowledge sharing in the scholarly world. Although many movements have been initiated in recent years, non-technical scientific communities suffer from transforming document-based publishing to knowledge-based publishing. In this paper, we present a model (PharmSci) for scholarly publishing in the pharmaceutical research domain with the goal of facilitating knowledge discovery through effective ontology-based data integration. PharmSci provides machine-interpretable information to the knowledge discovery process. The principles and guidelines of the ontological engineering have been followed. Reasoning-based techniques are also presented in the design of the ontology to improve the quality of targeted tasks for data integration. The developed ontology is evaluated with a validation process and also a quality verification method.

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Notes

  1. 1.

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

  2. 2.

    https://github.com/ZeynepSay/PharmSci/tree/master/CorpusData.

  3. 3.

    https://scholar.google.com/.

  4. 4.

    https://www.sciencedirect.com/.

  5. 5.

    https://www.w3.org/TR/owl2-overview/.

  6. 6.

    https://bioportal.bioontology.org/.

  7. 7.

    http://www.ontobee.org/.

  8. 8.

    http://www.obofoundry.org/.

  9. 9.

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

  10. 10.

    https://github.com/ZeynepSay/PharmSci/tree/master/CorpusData.

  11. 11.

    https://scigraph.springernature.com/explorer.

  12. 12.

    https://www.nlm.nih.gov/mesh/meshhome.html.

  13. 13.

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

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Acknowledgments

This work has been supported by ERC project ScienceGRAPH no. 819536, and the EPSRC grant EP/M025268/1, the WWTF grant VRG18-013, the EC Horizon 2020 grant LAMBDA (GA no. 809965), the CLEOPATRA project (GA no. 812997), and the German national funded BmBF project MLwin.

Author information

Authors and Affiliations

  1. Smart Data Analytics (SDA), University of Bonn, Bonn, Germany

    Zeynep Say, Said Fathalla, Sahar Vahdati & Jens Lehmann

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

    Said Fathalla

  3. Department of Computer Science, University of Oxford, Oxford, UK

    Sahar Vahdati

  4. Fraunhofer IAIS, Dresden, Germany

    Jens Lehmann

  5. TIB Leibniz Information Center for Science and Technology, Hannover, Germany

    Sören Auer

Authors
  1. Zeynep Say
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  2. Said Fathalla
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  3. Sahar Vahdati
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  4. Jens Lehmann
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  5. Sören Auer
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Corresponding author

Correspondence to Zeynep Say .

Editor information

Editors and Affiliations

  1. School of Computing and Communications, The Open University, Milton Keynes, UK

    Mark Hall

  2. Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia

    Tanja Merčun

  3. University Library J. C. Senckenberg, Goethe University Frankfurt, Frankfurt am Main, Germany

    Thomas Risse

  4. Université Claude Bernard Lyon 1, Villeurbanne, France

    Fabien Duchateau

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Say, Z., Fathalla, S., Vahdati, S., Lehmann, J., Auer, S. (2020). Ontology Design for Pharmaceutical Research Outcomes. In: Hall, M., Merčun, T., Risse, T., Duchateau, F. (eds) Digital Libraries for Open Knowledge. TPDL 2020. Lecture Notes in Computer Science(), vol 12246. Springer, Cham. https://doi.org/10.1007/978-3-030-54956-5_9

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  • DOI: https://doi.org/10.1007/978-3-030-54956-5_9

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