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Farghaly, K, Abanda, F, Vidalakis, C and Wood, G (2019) BIM-linked data integration for asset management. Built Environment Project and Asset Management, 9(04), 489–502.

  • Type: Journal Article
  • Keywords: BIM; Building maintenance; Asset management; Information management; Information exchange; Building lifecycle;
  • ISBN/ISSN: 2044-124X
  • URL: https://doi.org/10.1108/BEPAM-11-2018-0136
  • Abstract:
    The purpose of this paper is to investigate the transfer of information from the building information modelling (BIM) models to either conventional or advanced asset management platforms using Linked Data. To achieve this aim, a process for generating Linked Data in the asset management context and its integration with BIM data is presented. Design/methodology/approach The research design employs a participatory action research (PAR) approach. The PAR approach utilized two qualitative data collection methods, namely; focus group and interviews to identify and evaluate the required standards for the mapping of different domains. Also prototyping which is an approach of Software Development Methodology is utilized to develop the ontologies and Linked Data. Findings The proposed process offers a comprehensive description of the required standards and classifications in construction domain, related vocabularies and object-oriented links to ensure the effective data integration between different domains. Also the proposed process demonstrates the different stages, tools, best practices and guidelines to develop Linked Data, armed with a comprehensive use case Linked Data generation about building assets that consume energy. Originality/value The Linked Data generation and publications in the domain of AECO is still in its infancy and it also needs methodological guidelines to support its evolution towards maturity in its processes and applications. This research concentrates on the Linked Data applications with BIM to link across domains where few studies have been conducted.

Jafari, A and Akhavian, R (2019) Driving forces for the US residential housing price: a predictive analysis. Built Environment Project and Asset Management, 9(04), 515–29.

Madanayake, U H and Egbu, C (2019) Critical analysis for big data studies in construction: significant gaps in knowledge. Built Environment Project and Asset Management, 9(04), 530–47.

Marzouk, M and Enaba, M (2019) Analyzing project data in BIM with descriptive analytics to improve project performance. Built Environment Project and Asset Management, 9(04), 476–88.

Mitra, A and Munir, K (2019) Influence of Big Data in managing cyber assets. Built Environment Project and Asset Management, 9(04), 503–14.

Ram, J, Afridi, N K and Khan, K A (2019) Adoption of Big Data analytics in construction: development of a conceptual model. Built Environment Project and Asset Management, 9(04), 564–79.

Yap, J Y L, Ho, C C and Ting, C (2019) A systematic review of the applications of multi-criteria decision-making methods in site selection problems. Built Environment Project and Asset Management, 9(04), 548–63.