Clustering and ontology-based information integration framework for surface subsidence risk mitigation in underground tunnels

Du, J; He, R; Sugumaran, V

Clustering and ontology-based information integration framework for surface subsidence risk mitigation in underground tunnels

Du, J

He, R Sugumaran, V

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Publisher:: SPRINGER
Publication Type:: Journal Article
Citation:: Cluster Computing, 2016, 19, (4), pp. 2001-2014
Issue Date:: 2016-12-01

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Field	Value	Language
dc.contributor.author	Du, J https://orcid.org/0000-0002-6428-7763
dc.contributor.author	He, R
dc.contributor.author	Sugumaran, V
dc.date.accessioned	2022-02-14T21:28:35Z
dc.date.available	2022-02-14T21:28:35Z
dc.date.issued	2016-12-01
dc.identifier.citation	Cluster Computing, 2016, 19, (4), pp. 2001-2014
dc.identifier.issn	1386-7857
dc.identifier.issn	1573-7543
dc.identifier.uri	http://hdl.handle.net/10453/154505
dc.description.abstract	Building information modeling brings a fundamental technological innovation to the traditional architecture industry, which can optimize the construction process and improve the efficiency and effectiveness of the overall building process. Based on the information exchange of heterogeneous information systems and data around different stages of the whole life cycle of a building project, this article analyses the current state of building information interoperability and proposes an ontology-based information integration framework. In addition, hierarchical clustering method is used to analyze and find risk factors for surface subsidence in an underground tunnel construction project, and the results input into the information integration framework. The proposed approach maps the industry foundation classes data and relationships to an ontology, and utilizes an ontology-based reasoning model. An ontology for the underground tunnel has been developed using Protégé and a Jena inference engine has been developed to investigate the early warning signs of ground subsidence.
dc.language	English
dc.publisher	SPRINGER
dc.relation.ispartof	Cluster Computing
dc.relation.isbasedon	10.1007/s10586-016-0631-4
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0805 Distributed Computing
dc.subject.classification	Distributed Computing
dc.title	Clustering and ontology-based information integration framework for surface subsidence risk mitigation in underground tunnels
dc.type	Journal Article
utslib.citation.volume	19
utslib.for	0805 Distributed Computing
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
dc.date.updated	2022-02-14T21:28:33Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	19
utslib.citation.issue	4

Abstract:

Building information modeling brings a fundamental technological innovation to the traditional architecture industry, which can optimize the construction process and improve the efficiency and effectiveness of the overall building process. Based on the information exchange of heterogeneous information systems and data around different stages of the whole life cycle of a building project, this article analyses the current state of building information interoperability and proposes an ontology-based information integration framework. In addition, hierarchical clustering method is used to analyze and find risk factors for surface subsidence in an underground tunnel construction project, and the results input into the information integration framework. The proposed approach maps the industry foundation classes data and relationships to an ontology, and utilizes an ontology-based reasoning model. An ontology for the underground tunnel has been developed using Protégé and a Jena inference engine has been developed to investigate the early warning signs of ground subsidence.

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http://hdl.handle.net/10453/154505