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Enriching Scholarly Knowledge with Context

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Web Engineering (ICWE 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13362))

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Abstract

Leveraging a GraphQL-based federated query service that integrates multiple scholarly communication infrastructures (specifically, DataCite, ORCID, ROR, OpenAIRE, Semantic Scholar, Wikidata and Altmetric), we develop a novel web widget based approach for the presentation of scholarly knowledge with rich contextual information. We implement the proposed approach in the Open Research Knowledge Graph (ORKG) and showcase it on three kinds of widgets. First, we devise a widget for the ORKG paper view that presents contextual information about related datasets, software, project information, topics, and metrics. Second, we extend the ORKG contributor profile view with contextual information including authored articles, developed software, linked projects, and research interests. Third, we advance ORKG comparison faceted search by introducing contextual facets (e.g. citations). As a result, the devised approach enables presenting ORKG scholarly knowledge flexibly enriched with contextual information sourced in a federated manner from numerous technologically heterogeneous scholarly communication infrastructures.

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Notes

  1. 1.

    https://www.orkg.org/orkg/.

  2. 2.

    https://datacite.org/.

  3. 3.

    https://www.geonames.org/.

  4. 4.

    https://www.orkg.org/orkg/graphql-federated.

  5. 5.

    https://graph.openaire.eu/develop/api.html.

  6. 6.

    https://www.semanticscholar.org/product/api.

  7. 7.

    https://www.wikidata.org/w/api.php.

  8. 8.

    https://api.altmetric.com/.

  9. 9.

    http://www.epimorphics.com/web/tools/elda.html.

  10. 10.

    https://code.google.com/p/linkeddata-api.

  11. 11.

    https://scholexplorer.openaire.eu/.

  12. 12.

    https://www.wikidata.org/wiki/Wikidata:Main_Page.

  13. 13.

    https://openknowledgemaps.org/about.

  14. 14.

    https://unpaywall.org/.

  15. 15.

    https://zenodo.org/.

  16. 16.

    https://figshare.com/.

  17. 17.

    https://www.re3data.org/.

  18. 18.

    https://api.datacite.org/graphql.

  19. 19.

    https://commons.datacite.org/.

  20. 20.

    https://www.semanticscholar.org/.

  21. 21.

    https://www.altmetric.com/.

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Acknowledgment

This work was co-funded by the European Research Council for the project ScienceGRAPH (Grant agreement ID: 819536) and TIB–Leibniz Information Centre for Science and Technology.

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Authors and Affiliations

  1. L3S Research Center, Leibniz University Hannover, 30167, Hannover, Germany

    Muhammad Haris & Sören Auer

  2. TIB—Leibniz Information Centre for Science and Technology, Hannover, Germany

    Markus Stocker & Sören Auer

Authors
  1. Muhammad Haris
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  2. Markus Stocker
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Correspondence to Muhammad Haris .

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Editors and Affiliations

  1. Polytechnic University of Bari, Bari, Italy

    Tommaso Di Noia

  2. Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (Republic of)

    In-Young Ko

  3. Johannes Kepler University Linz, Linz, Austria

    Markus Schedl

  4. Polytechnic University of Bari, Bari, Italy

    Carmelo Ardito

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Haris, M., Stocker, M., Auer, S. (2022). Enriching Scholarly Knowledge with Context. In: Di Noia, T., Ko, IY., Schedl, M., Ardito, C. (eds) Web Engineering. ICWE 2022. Lecture Notes in Computer Science, vol 13362. Springer, Cham. https://doi.org/10.1007/978-3-031-09917-5_10

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  • DOI: https://doi.org/10.1007/978-3-031-09917-5_10

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