Details
| Original language | English |
|---|---|
| Title of host publication | Knowledge Engineering and Knowledge Management |
| Subtitle of host publication | 22nd International Conference, EKAW 2020, Bolzano, Italy, September 16-20, 2020 Proceedings |
| Editors | C. Maria Keet, Michel Dumontier |
| Place of Publication | Cham |
| Publisher | Springer Nature Switzerland AG |
| Pages | 271-286 |
| Number of pages | 16 |
| ISBN (electronic) | 9783030612443 |
| ISBN (print) | 9783030612436 |
| Publication status | Published - 27 Oct 2020 |
| Event | 22nd International Conference on Knowledge Engineering and Knowledge Management, EKAW 2020 - Bolzano, Italy Duration: 16 Sept 2020 → 20 Sept 2020 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 12387 |
| 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
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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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 proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Challenges of Linking Organizational Information in Open Government Data to Knowledge Graphs
AU - Portisch, Jan
AU - Fallatah, Omaima
AU - Neumaier, Sebastian
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.
PY - 2020/10/27
Y1 - 2020/10/27
N2 - 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.
AB - 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.
KW - Dataset evolution
KW - Entity linking
KW - Knowledge graph evolution
KW - Knowledge graphs
KW - Open data
UR - http://www.scopus.com/inward/record.url?scp=85096506734&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-61244-3_19
DO - 10.1007/978-3-030-61244-3_19
M3 - Conference contribution
AN - SCOPUS:85096506734
SN - 9783030612436
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 271
EP - 286
BT - Knowledge Engineering and Knowledge Management
A2 - Keet, C. Maria
A2 - Dumontier, Michel
PB - Springer Nature Switzerland AG
CY - Cham
T2 - 22nd International Conference on Knowledge Engineering and Knowledge Management, EKAW 2020
Y2 - 16 September 2020 through 20 September 2020
ER -