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Construction risk knowledge management in BIM using ontology and semantic web technology

Ding, L.Y., Zhong, B.T., Wu, Song and Luo, H.B. (2016) Construction risk knowledge management in BIM using ontology and semantic web technology. Safety Science, 87. pp. 202-213. ISSN 09257535

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Abstract

The development of Building Information Modelling provides a visual and information-rich environment to incorporate the construction risk knowledge in the domain of safety management. Ontology and semantic web technology offer an opportunity to enable such domain knowledge to be represented semantically. This paper attempts to take advantage of the strength of BIM, ontology and semantic web technology to establish an ontology-based methodology/framework for construction risk knowledge management in BIM environment. The risk knowledge is modelled into an ontology-based semantic network to produce a risk map, from which the interdependences between risks, risk paths can be inferred semantically. Based on the semantic retrieval mechanism, the applicable knowledge is dynamically linked to the specific objects in the BIM environment. Based on the methodology, a prototype system is developed as a tool to facilitate the construction risk knowledge management and reuse in hope of indirectly improving the construction risk analysis process. A case application is implemented to demonstrate the risk prevention through construction process/method selection, including the risk factors identification, risk paths reasoning and risk prevention plan recommendation. Finally, a questionnaire survey highlights the potential benefits and limitations on the deployment of such system.

Item Type: Article
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
T Technology > TH Building construction
Schools: School of Art, Design and Architecture
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Depositing User: Sara Taylor
Date Deposited: 20 Dec 2016 10:05
Last Modified: 07 Jan 2017 06:01
URI: http://eprints.hud.ac.uk/id/eprint/30788

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