BIM-linked data integration for asset management

Abstract

Purpose 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.

Construction safety ontology development and alignment with industry foundation classes (IFC)

“…As noted by (Ding et al, 2016), an ontology can offer three main benefits in knowledge modelling and management: 1) improve model flexibility and extendibility; 2) provide a robust semantic representation; and 3) enhance knowledge retrieval by improving the retrieval requests from the concept level. Consequently, several researchers have adopted ontology and Linked Data in various applications for the AECO sector, such as cross-domain information integration for Building Information Modelling (BIM) open standards (Torma, 2015) , cost estimation (Abanda,Kamsu-Foguem and Tah, 2017), manufacturing (An et al, 2019), asset management (Farghaly et al, 2019), energy management (Corry et al, 2015, Tomašević et al, 2015, Look ahead planning (Soman,Molina-Solana and Whyte, 2020) and crowd simulation (Boje, 2019).…”

“…This approach was utilised because software applications are commonly built on different geometry kernels, producing inaccuracies when transferring complex, mathematical geometry descriptions from one application to the other. Other work proposed developing several ontologies based on available standards such as Uniclass2 and NRM 1&3 to cross-map the datasets in BIM and asset management platforms (Farghaly et al, 2019). For heat loss calculation, Rasmussen et al (2019) developed an Ontology for Property Management (OPM) and proposed a semantic bridge with project-specific extensions of the Building Topology Ontology (BOT) and other work developed the integration between integrating BIM and product manufacture data (Niknam,Jalaei and Karshenas, 2019).…”

Data-Driven Construction Safety Information Sharing System Based on Linked Data, Ontologies, and Knowledge Graph Technologies

“…In AEC contexts, linked data and graph-based technologies can boost digitalization and knowledge creation [ 40 ], and a few studies have explored these potentials. Research efforts have developed semantic web- and graph-based applications to improve processes in quality management and defect prevention [ 16 ], construction procurement [ 41 ], asset management [ 42 ], building energy performance management [ 43 ], knowledge management [ 44 ], and look-ahead planning [ 45 ]. While linked data have been used to improve interoperability and link across domains in AEC research [ 46 ], scholarly efforts have barely delved into the potentials for construction safety information sharing.…”

Digital information technologies for prevention through design (PtD): a literature review and directions for future research

“…More than 85% of the papers were published in the time span from 2012 till 2020. The possible explanation for such a trend could be due to the growing adoption of advanced digital technologies in the construction industry, such as text mining, NoSQL databases and BIM for clash detection (Tixier et al, 2017), scheduling, and asset management (Farghaly et al, 2019). The trend of AI and digital transformation has increased significantly jumping form 1370 papers in 2010 to 5605 papers in 2018 (Darko et al, 2020).…”