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OmniScience and Extensions – Lessons Learned from Designing a Multi-domain, Multi-use Case Knowledge Representation System

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Knowledge Engineering and Knowledge Management (EKAW 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11313))

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Abstract

With growing research across scientific domains and increasing daily publications volumes, it is essential to provide our users, at Elsevier, with up to date, comprehensive and to the point data. One of the key aspects of that offer is to have a global Knowledge Organization System (KOS) overarching scientific branches but also going deep enough into each domain to provide rich annotation or classification capacities. Knowing that the endeavor of creating one global “ontology of everything” is an utopia, we designed a dual/multi-vocabulary model where domain-specific extensions can be used in junction with a high-to-mid-level KOS covering the broad spectrum of scientific research. In this paper, we present our design model along with our updating procedure and our lessons learned in different use cases: the Evise submission system, the Topic Pages project and a Semantic Annotation Proof of Concept experiment in the field of Engineering.

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Notes

  1. 1.

    For example: https://www.sciencedirect.com/science/referenceworks/9780124095489.

  2. 2.

    https://www.elsevier.com/about/press-releases/science-and-technology/elsevier-launches-sciencedirect-topics-to-help-researchers-quickly-build-their-knowledge-and-save-valuable-time-searching.

  3. 3.

    http://sciencedirect.com/.

  4. 4.

    https://www.mendeley.com/.

  5. 5.

    We chose to focus on these two use cases as these are the most visible for the international community and cover the requirements that are derived from the crosswalk use case.

  6. 6.

    https://www.elsevier.com/en-gb/editors/evise.

  7. 7.

    https://www.journals.elsevier.com/heliyon.

  8. 8.

    https://www.journals.elsevier.com/iscience.

  9. 9.

    https://cso.kmi.open.ac.uk.

  10. 10.

    https://www.elsevier.com/solutions/sciencedirect/topics.

  11. 11.

    https://www.w3.org/.

  12. 12.

    https://www.w3.org/TR/rdf-schema/#ch_type.

  13. 13.

    http://dublincore.org/documents/dcmi-terms/#terms-source.

  14. 14.

    http://lemon-model.net/.

  15. 15.

    https://www.sciencedirect.com/science?_ob=MiamiSearchURL&_method=requestForm&_temp=all_boolSearch.tmpl&md5=052b06d957a9d8c82e07acf1d7eef1b7.

  16. 16.

    http://id.loc.gov/authorities/subjects.html.

  17. 17.

    https://github.com/PLOS/plos-thesaurus/blob/develop/README.md.

  18. 18.

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

  19. 19.

    http://wndomains.fbk.eu/.

  20. 20.

    https://www.mpi-inf.mpg.de/departments/databases-and-information-systems/research/yago-naga/yago/.

  21. 21.

    https://gist.github.com/soeffing/b0e026fd597015826d1a389ac739212f.

  22. 22.

    https://pypi.org/project/gensim/.

  23. 23.

    http://lucene.apache.org/solr/.

  24. 24.

    https://www.elsevier.com/en-gb/solutions/knovel-engineering-information.

  25. 25.

    https://www.nltk.org/.

  26. 26.

    https://pandas.pydata.org/.

References

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Acknowledgements

Our thanks go our colleagues Anique van Berne, Subhradeep Kayal and Till Bey for AnAGram, the Trending and Influential Topics extraction and the Koalas Python module; the teams we interact with on a daily basis: Akileshwari Chandrasekhar, Olga Fedorova, Marleen Rodenburg, Anda Grigorescu, Marcela Haldan, Monica Paravidino, Jenny Truong and Georgios Tsatsaronis.

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Authors and Affiliations

  1. Elsevier BV, 1043 NX, Amsterdam, Netherlands

    Véronique Malaisé, Anke Otten & Pascal Coupet

Authors
  1. Véronique Malaisé
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  2. Anke Otten
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  3. Pascal Coupet
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Corresponding author

Correspondence to Véronique Malaisé .

Editor information

Editors and Affiliations

  1. Université Côte d’Azur, CNRS, Inria, I3S, Sophia Antipolis, France

    Catherine Faron Zucker

  2. Fondazione Bruno Kessler, Trento, Italy

    Chiara Ghidini

  3. University of Lorraine, CNRS, Inria, LORIA, Nancy, France

    Amedeo Napoli

  4. University of Lorraine, CNRS, Inria, LORIA, Nancy, France

    Yannick Toussaint

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Malaisé, V., Otten, A., Coupet, P. (2018). OmniScience and Extensions – Lessons Learned from Designing a Multi-domain, Multi-use Case Knowledge Representation System. In: Faron Zucker, C., Ghidini, C., Napoli, A., Toussaint, Y. (eds) Knowledge Engineering and Knowledge Management. EKAW 2018. Lecture Notes in Computer Science(), vol 11313. Springer, Cham. https://doi.org/10.1007/978-3-030-03667-6_15

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  • DOI: https://doi.org/10.1007/978-3-030-03667-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03666-9

  • Online ISBN: 978-3-030-03667-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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