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An Analysis of Links in Wikidata

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The Semantic Web (ESWC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13261))

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Abstract

Wikidata has become one of the most prominent open knowledge graphs (KGs) on the Web. Relying on a community of users with different expertise, this cross-domain KG is directly related to other data sources. This paper investigates how Wikidata is linked to other data sources in the Linked Data ecosystem. To this end, we adapt previous definitions of ontology links and instance links to the terminological part of the Wikidata vocabulary and perform an analysis of the links in Wikidata to external datasets and ontologies from the Linked Data ecosystem. As a side effect, this reveals insights on the ontological expressiveness of meta-properties used in Wikidata. The results of this analysis show that while Wikidata defines a large number of individuals, classes and properties within its own namespace, they are not (yet) extensively linked. We discuss reasons for this and conclude with some suggestions to increase the interconnectedness of Wikidata with other KGs.

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Notes

  1. 1.

    cf. https://www.wikidata.org/wiki/Special:Statistics.

  2. 2.

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

  3. 3.

    https://www.rdfhdt.org/datasets/.

  4. 4.

    For instance, the pattern {[] wdt:P279 ?X; wdt:P31 ?X.} indicates ambiguous subclass vs. instance of usage on 2131 entities, run on 9 Dec 2021 at https://w.wiki/4XQw.

  5. 5.

    See https://www.wikidata.org/wiki/Wikidata:WikiProject_Ontology/Top-level_ontology_list for the top two layers of the ontology.

  6. 6.

    i.e., there are 37 uses of P2445 in total in Wikidata as of August 2021.

  7. 7.

    There are higher orders of second-order class, i.e., third-, fourth- and fifth-order classes, each of which is an instance of the higher ordered class, all of which are subclasses of the fixed-order class (Q23959932).

  8. 8.

    cf. https://www.w3.org/TR/owl2-new-features/#Simple_metamodeling_capabilities.

  9. 9.

    cf. https://www.wikidata.org/wiki/Wikidata:List_of_properties/Wikidata_property_for_properties.

  10. 10.

    We note here again that subtle semantic differences such as constraining (i.e., CWA) vs implicit (i.e., OWA) semantics of certain properties are not relevant for the purpose of our link analysis.

  11. 11.

    Prefixes are used as follows: wd: <http://www.wikidata.org/entity/>, wdt: <http://www.wikidata.org/prop/direct/>, pq: <http://www.wikidata.org/prop/qualifier/>, p: <http://www.wikidata.org/prop/>, ps: <http://www.wikidata.org/prop/statement/>.

  12. 12.

    https://www.wikidata.org/wiki/Wikidata:Property_proposal/disjoint_with.

  13. 13.

    All code implemented in Python is available at: https://github.com/arminhaller/LinksInLOD.

  14. 14.

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

  15. 15.

    No longitudional data is published on the Wikidata site, but the growth in the number of properties between July and November 2021 was 3.4%.

  16. 16.

    Some individuals might use more than one exact match relation.

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Acknowledgment

This research has received funding from the Teaming.AI project, which is part of the European Union’s Horizon 2020 research and innovation program under grant agreement No 957402.

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Authors and Affiliations

  1. Australian National University, Canberra, ACT, 2601, Australia

    Armin Haller & Sergio J. Rodríguez Méndez

  2. Vienna University of Economics and Business, Vienna, Austria

    Axel Polleres, Daniil Dobriy & Nicolas Ferranti

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  1. Armin Haller
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  2. Axel Polleres
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  3. Daniil Dobriy
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  4. Nicolas Ferranti
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  5. Sergio J. Rodríguez Méndez
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Correspondence to Armin Haller .

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Editors and Affiliations

  1. University of Amsterdam, Amsterdam, Noord-Holland, The Netherlands

    Paul Groth

  2. Universidad Simón Bolívar, Leibniz Information Centre for Science and Technology, Hannover, Niedersachsen, Germany

    Maria-Esther Vidal

  3. Institut Polytechnique de Paris "DIG", Télécom ParisTech, Palaiseau, France

    Fabian Suchanek

  4. University of Southern California, Marina del Rey, CA, USA

    Pedro Szekley

  5. IBM Research - Thomas J. Watson Research, Yorktown Heights, NY, USA

    Pavan Kapanipathi

  6. LaSIGE, Fac de Ciencias,Edif C6, Pis0 3, Universidade de Lisboa, Lisbon, Portugal

    Catia Pesquita

  7. University of Nantes, Nantes, France

    Hala Skaf-Molli

  8. Aalto University, Espoo, Finland

    Minna Tamper

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Haller, A., Polleres, A., Dobriy, D., Ferranti, N., Rodríguez Méndez, S.J. (2022). An Analysis of Links in Wikidata. In: Groth, P., et al. The Semantic Web. ESWC 2022. Lecture Notes in Computer Science, vol 13261. Springer, Cham. https://doi.org/10.1007/978-3-031-06981-9_2

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  • DOI: https://doi.org/10.1007/978-3-031-06981-9_2

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