Challenges of Linking Organizational Information in Open Government Data to Knowledge Graphs

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

  • Jan Portisch
  • Omaima Fallatah
  • Sebastian Neumaier
  • Mohamad Yaser Jaradeh
  • Axel Polleres

Research Organisations

External Research Organisations

  • University of Mannheim
  • The University of Sheffield
  • WU (Vienna University of Economics and Business)
  • Complexity Science Hub Vienna (CSH)
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Details

Original languageEnglish
Title of host publicationKnowledge Engineering and Knowledge Management
Subtitle of host publication22nd International Conference, EKAW 2020, Bolzano, Italy, September 16-20, 2020 Proceedings
EditorsC. Maria Keet, Michel Dumontier
Place of PublicationCham
PublisherSpringer Nature Switzerland AG
Pages271-286
Number of pages16
Edition1.
ISBN (electronic)9783030612443
ISBN (print)9783030612436
Publication statusPublished - 27 Oct 2020
Event22nd International Conference on Knowledge Engineering and Knowledge Management, EKAW 2020 - Bolzano, Italy
Duration: 16 Sept 202020 Sept 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12387
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Abstract

Open Government Data (OGD) is being published by various public administration organizations around the globe. Within the metadata of OGD data catalogs, the publishing organizations (1) are not uniquely and unambiguously identifiable and, even worse, (2) change over time, by public administration units being merged or restructured. In order to enable fine-grained analyzes or searches on Open Government Data on the level of publishing organizations, linking those from OGD portals to publicly available knowledge graphs (KGs) such as Wikidata and DBpedia seems like an obvious solution. Still, as we show in this position paper, organization linking faces significant challenges, both in terms of available (portal) metadata and KGs in terms of data quality and completeness. We herein specifically highlight five main challenges, namely regarding (1) temporal changes in organizations and in the portal metadata, (2) lack of a base ontology for describing organizational structures and changes in public knowledge graphs, (3) metadata and KG data quality, (4) multilinguality, and (5) disambiguating public sector organizations. Based on available OGD portal metadata from the Open Data Portal Watch, we provide an in-depth analysis of these issues, make suggestions for concrete starting points on how to tackle them along with a call to the community to jointly work on these open challenges.

Keywords

    Dataset evolution, Entity linking, Knowledge graph evolution, Knowledge graphs, Open data

ASJC Scopus subject areas

Cite this

Challenges of Linking Organizational Information in Open Government Data to Knowledge Graphs. / Portisch, Jan; Fallatah, Omaima; Neumaier, Sebastian et al.
Knowledge Engineering and Knowledge Management: 22nd International Conference, EKAW 2020, Bolzano, Italy, September 16-20, 2020 Proceedings. ed. / C. Maria Keet; Michel Dumontier. 1. ed. Cham: Springer Nature Switzerland AG, 2020. p. 271-286 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12387).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Portisch, J, Fallatah, O, Neumaier, S, Jaradeh, MY & Polleres, A 2020, Challenges of Linking Organizational Information in Open Government Data to Knowledge Graphs. in CM Keet & M Dumontier (eds), Knowledge Engineering and Knowledge Management: 22nd International Conference, EKAW 2020, Bolzano, Italy, September 16-20, 2020 Proceedings. 1. edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12387, Springer Nature Switzerland AG, Cham, pp. 271-286, 22nd International Conference on Knowledge Engineering and Knowledge Management, EKAW 2020, Bolzano, Italy, 16 Sept 2020. https://doi.org/10.1007/978-3-030-61244-3_19, https://doi.org/10.1007/978-3-030-61244-3_19
Portisch, J., Fallatah, O., Neumaier, S., Jaradeh, M. Y., & Polleres, A. (2020). Challenges of Linking Organizational Information in Open Government Data to Knowledge Graphs. In C. M. Keet, & M. Dumontier (Eds.), Knowledge Engineering and Knowledge Management: 22nd International Conference, EKAW 2020, Bolzano, Italy, September 16-20, 2020 Proceedings (1. ed., pp. 271-286). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12387). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-61244-3_19, https://doi.org/10.1007/978-3-030-61244-3_19
Portisch J, Fallatah O, Neumaier S, Jaradeh MY, Polleres A. Challenges of Linking Organizational Information in Open Government Data to Knowledge Graphs. In Keet CM, Dumontier M, editors, Knowledge Engineering and Knowledge Management: 22nd International Conference, EKAW 2020, Bolzano, Italy, September 16-20, 2020 Proceedings. 1. ed. Cham: Springer Nature Switzerland AG. 2020. p. 271-286. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-61244-3_19, 10.1007/978-3-030-61244-3_19
Portisch, Jan ; Fallatah, Omaima ; Neumaier, Sebastian et al. / Challenges of Linking Organizational Information in Open Government Data to Knowledge Graphs. Knowledge Engineering and Knowledge Management: 22nd International Conference, EKAW 2020, Bolzano, Italy, September 16-20, 2020 Proceedings. editor / C. Maria Keet ; Michel Dumontier. 1. ed. Cham : Springer Nature Switzerland AG, 2020. pp. 271-286 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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AU - Jaradeh, Mohamad Yaser

AU - Polleres, Axel

N1 - Funding Information: The authors thank Vincent Emonet, Paola Espinoza-Arias, and Bilal Koteich who contributed preliminary analyses regarding the challenges addressed in this paper. We also thank the organizers of the International Semantic Web Summer school (ISWS) 2019: the idea for this paper origins in discussions at the school.

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