Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400, Beach, Thomas ORCID: https://orcid.org/0000-0001-5610-8027 and Rana, Omer Farooq ORCID: https://orcid.org/0000-0003-3597-2646 2013. A governance approach for BIM management across lifecycle and supply chains using mixed-modes of information delivery. Journal of Civil Engineering and Management 19 (2) , pp. 239-258. 10.3846/13923730.2012.760480 |
Abstract
Built environment data is of varying nature embedding various forms of sensitivities with potential legal, contractual, intellectual property, and security implications. The paper presents a governance approach for managing multi-actor, multi-discipline, and total lifecycle data, informed by a wide industry consultation conducted in the UK between March and September 2011. The study identifies a number of barriers in engaging with Building Information Modelling (BIM) efforts with a view of facilitating collaboration around a common and integrated project specification. A governance model is proposed that addresses the identified adoption blockers underpinned by a “mixed approach”, that factors in various modes of information delivery, ranging from paper-based documents to object-based information conveyed by IFC (Industry Foundation Classes). A demonstrator system is developed and used to validate our BIM governance concepts. Our governance model is discussed in the context of the recent UK government BIM industry consultation document supported by a research and development (R&D) roadmap taking into account current industry structure and its various levels of stakeholders’ maturity, capability and readiness.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Advanced Research Computing @ Cardiff (ARCCA) Computer Science & Informatics Engineering |
Subjects: | H Social Sciences > HD Industries. Land use. Labor Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Uncontrolled Keywords: | BIM, governance, supply chain, lifecycle, data storage |
Publisher: | Taylor & Francis |
ISSN: | 1392-3730 |
Funders: | EPSRC |
Last Modified: | 21 Oct 2022 10:01 |
URI: | https://orca.cardiff.ac.uk/id/eprint/38703 |
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