Research on Semantic Driven Urban Pipeline Dataspace Construction Method

Urban pipeline data is heterogeneous in multiple sources and rich in data volume, and there are problems such as data conflict and difficult organization and management due to the heterogeneity of multiple sources when accessing the data in large-scale concurrently. To address this problem, this pap...

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Main Authors: B. Li, L. Huo, Y. Yang, P. Bao, M. Zhang, Y. Li
Format: Article
Language:English
Published: Copernicus Publications 2024-10-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://isprs-annals.copernicus.org/articles/X-4-2024/189/2024/isprs-annals-X-4-2024-189-2024.pdf
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author B. Li
L. Huo
Y. Yang
P. Bao
M. Zhang
Y. Li
author_facet B. Li
L. Huo
Y. Yang
P. Bao
M. Zhang
Y. Li
author_sort B. Li
collection DOAJ
description Urban pipeline data is heterogeneous in multiple sources and rich in data volume, and there are problems such as data conflict and difficult organization and management due to the heterogeneity of multiple sources when accessing the data in large-scale concurrently. To address this problem, this paper proposes a semantics-driven urban pipeline dataspace construction method, which aims to realize the efficient organization of pipeline data. Firstly, this method combines the classification and characteristics of urban pipelines, and expresses the semantic information of pipeline geographic entities from four dimensions: semantic description, spatial location, attribute characteristics and time evolution. Then, the four expression sets are embedded into the dataspace RDF model as predicates, and the associated description mechanism of pipeline geographic entities is established by means of genus classes and so on, so as to construct the pipeline dataspace RDF model. Finally, the model is stored and graphically visualized using neo4j to achieve fast retrieval of data within the pipeline dataspace. The research results show that this method provides a unified expression of pipeline entities, solves the problem of pipeline multi-source heterogeneous data conflict and organization difficulties, and improves the efficiency of multi-source heterogeneous pipeline data organization while ensuring the integrity of pipeline information to the maximum extent.
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issn 2194-9042
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publishDate 2024-10-01
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series ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
spelling doaj-art-c10e80d157e6471bb981bfbbef36cf352025-08-20T01:48:02ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502024-10-01X-4-202418919410.5194/isprs-annals-X-4-2024-189-2024Research on Semantic Driven Urban Pipeline Dataspace Construction MethodB. Li0L. Huo1Y. Yang2P. Bao3M. Zhang4Y. Li5Beijing University of Civil Engineering and Architecture, Beijing, ChinaBeijing University of Civil Engineering and Architecture, Beijing, ChinaState Geospatial Information Center, Beijing, ChinaCIGIS (CHINA) LIMITED, Beijing, ChinaBeijing University of Civil Engineering and Architecture, Beijing, ChinaBeijing University of Civil Engineering and Architecture, Beijing, ChinaUrban pipeline data is heterogeneous in multiple sources and rich in data volume, and there are problems such as data conflict and difficult organization and management due to the heterogeneity of multiple sources when accessing the data in large-scale concurrently. To address this problem, this paper proposes a semantics-driven urban pipeline dataspace construction method, which aims to realize the efficient organization of pipeline data. Firstly, this method combines the classification and characteristics of urban pipelines, and expresses the semantic information of pipeline geographic entities from four dimensions: semantic description, spatial location, attribute characteristics and time evolution. Then, the four expression sets are embedded into the dataspace RDF model as predicates, and the associated description mechanism of pipeline geographic entities is established by means of genus classes and so on, so as to construct the pipeline dataspace RDF model. Finally, the model is stored and graphically visualized using neo4j to achieve fast retrieval of data within the pipeline dataspace. The research results show that this method provides a unified expression of pipeline entities, solves the problem of pipeline multi-source heterogeneous data conflict and organization difficulties, and improves the efficiency of multi-source heterogeneous pipeline data organization while ensuring the integrity of pipeline information to the maximum extent.https://isprs-annals.copernicus.org/articles/X-4-2024/189/2024/isprs-annals-X-4-2024-189-2024.pdf
spellingShingle B. Li
L. Huo
Y. Yang
P. Bao
M. Zhang
Y. Li
Research on Semantic Driven Urban Pipeline Dataspace Construction Method
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title Research on Semantic Driven Urban Pipeline Dataspace Construction Method
title_full Research on Semantic Driven Urban Pipeline Dataspace Construction Method
title_fullStr Research on Semantic Driven Urban Pipeline Dataspace Construction Method
title_full_unstemmed Research on Semantic Driven Urban Pipeline Dataspace Construction Method
title_short Research on Semantic Driven Urban Pipeline Dataspace Construction Method
title_sort research on semantic driven urban pipeline dataspace construction method
url https://isprs-annals.copernicus.org/articles/X-4-2024/189/2024/isprs-annals-X-4-2024-189-2024.pdf
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AT mzhang researchonsemanticdrivenurbanpipelinedataspaceconstructionmethod
AT yli researchonsemanticdrivenurbanpipelinedataspaceconstructionmethod