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A platform for research: civil engineering, architecture and urbanism
BIM and ontology-based knowledge management for dam safety monitoring
Abstract Dam Safety Monitoring Systems (DSMSs) are crucial in evaluating the operational state of dams. However, heterogeneous monitoring data distributed from multiple sources during the dam operation lacks a unified data integration method and prohibits knowledge extraction and intelligent analysis, which currently poses a labor-intensive task. To address this issue, a solution relying on Building Information Modeling (BIM) and domain ontologies is proposed. Specifically, a DSMS domain ontology (OntoDSMS) is developed by comprehensively collecting domain knowledge and extracting context information from the dam information model. Furthermore, a rule-based reasoner and SPARQL queries are implemented. The proposed approach facilitates the effective integration of dam safety monitoring information while reducing retrieval time effectively compared with traditional databases. A case is illustrated to demonstrate the feasibility and practicality of the proposed approach.
Highlights A framework combining BIM and ontology is proposed. A mapping between a Relational Database and an ontology is established. A domain ontology for Dam Safety Monitoring Systems is established and SPARQL queries are implemented. The proposed approach facilitates the effective integration of dam safety monitoring information.
BIM and ontology-based knowledge management for dam safety monitoring
Abstract Dam Safety Monitoring Systems (DSMSs) are crucial in evaluating the operational state of dams. However, heterogeneous monitoring data distributed from multiple sources during the dam operation lacks a unified data integration method and prohibits knowledge extraction and intelligent analysis, which currently poses a labor-intensive task. To address this issue, a solution relying on Building Information Modeling (BIM) and domain ontologies is proposed. Specifically, a DSMS domain ontology (OntoDSMS) is developed by comprehensively collecting domain knowledge and extracting context information from the dam information model. Furthermore, a rule-based reasoner and SPARQL queries are implemented. The proposed approach facilitates the effective integration of dam safety monitoring information while reducing retrieval time effectively compared with traditional databases. A case is illustrated to demonstrate the feasibility and practicality of the proposed approach.
Highlights A framework combining BIM and ontology is proposed. A mapping between a Relational Database and an ontology is established. A domain ontology for Dam Safety Monitoring Systems is established and SPARQL queries are implemented. The proposed approach facilitates the effective integration of dam safety monitoring information.
BIM and ontology-based knowledge management for dam safety monitoring
Zhou, Yuhang (author) / Bao, Tengfei (author) / Shu, Xiaosong (author) / Li, Yueyang (author) / Li, Yangtao (author)
2022-10-31
Article (Journal)
Electronic Resource
English
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