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An Ontology Framework for ERBS (Evidence/Risk-Based Safety) Management of Divisional and Subdivisional Works with High Risk
An Ontology Framework for ERBS (Evidence/Risk-Based Safety) Management of Divisional and Subdivisional Works with High Risk
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An Ontology Framework for ERBS (Evidence/Risk-Based Safety) Management of Divisional and Subdivisional Works with High Risk
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An Ontology Framework for ERBS (Evidence/Risk-Based Safety) Management of Divisional and Subdivisional Works with High Risk
An Ontology Framework for ERBS (Evidence/Risk-Based Safety) Management of Divisional and Subdivisional Works with High Risk

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An Ontology Framework for ERBS (Evidence/Risk-Based Safety) Management of Divisional and Subdivisional Works with High Risk
An Ontology Framework for ERBS (Evidence/Risk-Based Safety) Management of Divisional and Subdivisional Works with High Risk
Journal Article

An Ontology Framework for ERBS (Evidence/Risk-Based Safety) Management of Divisional and Subdivisional Works with High Risk

2024
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Overview
As an important data source, the Building Information Model (BIM) plays an important role in modern building safety management. Numerous studies have closely examined automatic compliance inspections for building safety and the safety management of dangerous projects. However, the value of the BIM has not been fully exploited in evidence-based practices of building safety. To address this limitation, this paper proposes an ontology-based Evidence/Risk-Based Safety (ERBS) management framework for divisional and subdivisional works with high risk, which includes: (1) BIM data extraction based on dynamo; (2) creation of an ontology based on building information and the ERBS management process model; (3) converting BIM data and evidence into ontology individuals; and (4) integrating the ontology through semantic web technology and using the Semantic Web Rule Language (SWRL) to conduct rule-based reasoning on the ontology. A case study shows that the framework is effective for the ERBS management of divisional and subdivisional works with high risk. The framework proposed in this study provides effective safety management methods for high-risk projects that can be applied in wider engineering practice in the future.