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Managing 3D GIS Data for Indoor Environment Using Property Graph Database

Authors
Jang, HanmeYu, KiyunPark, Seula
Issue Date
Apr-2023
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Keywords
Databases; Three-dimensional displays; Data models; Spatial databases; Geometry; Standards; Database systems; Graph database; indoorGML; indoor database; property graph model; 3D GIS data
Citation
IEEE Access, v.11, pp 37216 - 37228
Pages
13
Journal Title
IEEE Access
Volume
11
Start Page
37216
End Page
37228
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/91587
DOI
10.1109/access.2023.3266519
ISSN
2169-3536
Abstract
With the diversification of three-dimensional (3D) urban space data sources and data collection methods, the Open Geospatial Consortium published 3D spatial data standards in Geography Markup Language (GML). Among them, IndoorGML is a data model for expressing the topological relationship between indoor spaces with advantages in terms of semantic information storage and navigation applications. Conversion into a suitable binary file must be accomplished to use the IndoorGML documents through integration with other data. This study proposes a method of generating graph database objects from the documents of IndoorGML to promote usability and interoperability. The labeled property graph model is designed to reflect IndoorGML's multilayered graph concept. Moreover, in the proposed graph model, the geometry of physical indoor spaces is segregated into separate surfaces. All elements from IndoorGML are managed with specific labels in Neo4j, the most dominant graph database. By applying the proposed method, the graph database is constructed using the officially distributed IndoorGML documents of three buildings. The number of generated graph objects is determined to confirm whether the IndoorGML features are accurately converted into graph database objects. Furthermore, the utility of the constructed graph database is verified through two scenario-based routing tests consisting of finding the optimal room with the lowest route cost and allocating indoor spaces for patrolling to outdoor security offices through indoor and outdoor data integration. In conclusion, this study confirms that the utility of IndoorGML can be promoted using a graph database system in data integration, data queries, and pathfinding applications while preserving data topology and interoperability.
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Engineering (Department of Civil & Environmental Engineering)
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