Research on Semantic Driven Urban Pipeline Dataspace Construction Method - B. Li; L. Huo; Y. Yang; P. Bao; M. Zhang; Y. Li (ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences)
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.