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Sökning: WFRF:(Ding Yu Feng) > (2020-2024) > Integrating 3D city...

Integrating 3D city data through knowledge graphs

Ding, Linfang (författare)
Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Trondheim, Norway
Xiao, Guohui (författare)
Department of Information Science and Media Studies, University of Bergen, Bergen, Norway; Ontopic S.r.l, Bolzano, Italy
Pano, Albulen (författare)
Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, Italy
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Fumagalli, Mattia (författare)
Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, Italy
Chen, Dongsheng (författare)
Chair of Cartography and Visual Analytics, Technical University of Munich, Munich, Germany
Feng, Yu (författare)
Chair of Cartography and Visual Analytics, Technical University of Munich, Munich, Germany
Calvanese, Diego (författare)
Umeå universitet,Institutionen för datavetenskap,Ontopic S.r.l, Bolzano, Italy; Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, Italy
Fan, Hongchao (författare)
Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Trondheim, Norway
Meng, Liqiu (författare)
Chair of Cartography and Visual Analytics, Technical University of Munich, Munich, Germany
visa färre...
Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Trondheim, Norway Department of Information Science and Media Studies, University of Bergen, Bergen, Norway; Ontopic Sr.l, Bolzano, Italy (creator_code:org_t)
2024
2024
Engelska.
Ingår i: Geo-spatial Information Science. - : Taylor & Francis. - 1009-5020 .- 1993-5153.
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • CityGML is a widely adopted standard for representing and exchanging 3D city models. The representation of semantic and topological properties in CityGML makes it possible to query such 3D city data for analysis in various applications. Nevertheless, the potential of querying CityGML data has not been fully exploited. The official GML encoding of CityGML is mainly an information model used for data storage and exchange, but not suitable for performing complex queries. The most common way of dealing with CityGML data is to store them as tables in the 3DCityDB system. However, it remains a challenging task for end users to formulate SQL queries over 3DCityDB directly for their ad-hoc analytical tasks because of the gap between the semantics of CityGML and the relational schema adopted in 3DCityDB. The technology of Knowledge Graphs (KGs), where an ontology is at the core, is a good solution to bridge such a gap. Moreover, embracing KGs makes it easier to integrate with other spatial data sources, e.g. OpenStreetMap, and to perform queries combining information from multiple data sources. In this work, we describe a CityGML-KG framework to expose the CityGML data in 3DCityDB as a KG. To evaluate our approach, we use CityGML data from the city of Munich as a test area and integrate OpenStreetMap data.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Nyckelord

CityGML
data integration
geospatial knowledge graph
ontology
OpenStreetMap
query answering

Publikations- och innehållstyp

ref (ämneskategori)
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