WorldKG: A World-Scale Geographic Knowledge Graph

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

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  • Rheinische Friedrich-Wilhelms-Universität Bonn
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OriginalspracheEnglisch
Titel des SammelwerksCIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management
Seiten4475-4484
Seitenumfang10
ISBN (elektronisch)9781450384469
PublikationsstatusVeröffentlicht - 30 Okt. 2021
Veranstaltung30th ACM International Conference on Information and Knowledge Management, CIKM 2021 - Virtual, Online, Australien
Dauer: 1 Nov. 20215 Nov. 2021

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NameInternational Conference on Information and Knowledge Management, Proceedings

Abstract

OpenStreetMap is a rich source of openly available geographic information. However, the representation of geographic entities, e.g., buildings, mountains, and cities, within OpenStreetMap is highly heterogeneous, diverse, and incomplete. As a result, this rich data source is hardly usable for real-world applications. This paper presents WorldKG - a new geographic knowledge graph aiming to provide a comprehensive semantic representation of geographic entities in OpenStreetMap. We describe the WorldKG knowledge graph, including its ontology that builds the semantic dataset backbone, the extraction procedure of the ontology and geographic entities from OpenStreetMap, and the methods to enhance entity annotation. We perform statistical and qualitative dataset assessment, demonstrating the large scale and high precision of the semantic geographic information in WorldKG.

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WorldKG: A World-Scale Geographic Knowledge Graph. / Dsouza, Alishiba; Tempelmeier, Nicolas; Yu, Ran et al.
CIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management. 2021. S. 4475-4484 (International Conference on Information and Knowledge Management, Proceedings).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Dsouza, A, Tempelmeier, N, Yu, R, Gottschalk, S & Demidova, E 2021, WorldKG: A World-Scale Geographic Knowledge Graph. in CIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management. International Conference on Information and Knowledge Management, Proceedings, S. 4475-4484, 30th ACM International Conference on Information and Knowledge Management, CIKM 2021, Virtual, Online, Australien, 1 Nov. 2021. https://doi.org/10.48550/arXiv.2109.10036, https://doi.org/10.1145/3459637.3482023
Dsouza, A., Tempelmeier, N., Yu, R., Gottschalk, S., & Demidova, E. (2021). WorldKG: A World-Scale Geographic Knowledge Graph. In CIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management (S. 4475-4484). (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.48550/arXiv.2109.10036, https://doi.org/10.1145/3459637.3482023
Dsouza A, Tempelmeier N, Yu R, Gottschalk S, Demidova E. WorldKG: A World-Scale Geographic Knowledge Graph. in CIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management. 2021. S. 4475-4484. (International Conference on Information and Knowledge Management, Proceedings). doi: 10.48550/arXiv.2109.10036, 10.1145/3459637.3482023
Dsouza, Alishiba ; Tempelmeier, Nicolas ; Yu, Ran et al. / WorldKG : A World-Scale Geographic Knowledge Graph. CIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management. 2021. S. 4475-4484 (International Conference on Information and Knowledge Management, Proceedings).
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title = "WorldKG: A World-Scale Geographic Knowledge Graph",
abstract = "OpenStreetMap is a rich source of openly available geographic information. However, the representation of geographic entities, e.g., buildings, mountains, and cities, within OpenStreetMap is highly heterogeneous, diverse, and incomplete. As a result, this rich data source is hardly usable for real-world applications. This paper presents WorldKG - a new geographic knowledge graph aiming to provide a comprehensive semantic representation of geographic entities in OpenStreetMap. We describe the WorldKG knowledge graph, including its ontology that builds the semantic dataset backbone, the extraction procedure of the ontology and geographic entities from OpenStreetMap, and the methods to enhance entity annotation. We perform statistical and qualitative dataset assessment, demonstrating the large scale and high precision of the semantic geographic information in WorldKG.",
keywords = "knowledge graph, openstreetmap, semantic geospatial data",
author = "Alishiba Dsouza and Nicolas Tempelmeier and Ran Yu and Simon Gottschalk and Elena Demidova",
note = "Funding Information: Acknowledgements. This work was partially funded by DFG, German Research Foundation under “WorldKG” (424985896). ; 30th ACM International Conference on Information and Knowledge Management, CIKM 2021 ; Conference date: 01-11-2021 Through 05-11-2021",
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AU - Dsouza, Alishiba

AU - Tempelmeier, Nicolas

AU - Yu, Ran

AU - Gottschalk, Simon

AU - Demidova, Elena

N1 - Funding Information: Acknowledgements. This work was partially funded by DFG, German Research Foundation under “WorldKG” (424985896).

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