BIM for Facilities Management (BIM for FM) is a relatively new and growing topic of inquiry aiming to fulfil the informational needs of the operational phase of assets within increasingly digitalised project workflows. Research into the management of structured (i.e. graphical and non-graphical) and unstructured data (i.e. documents) has largely focused on design and construction phases. Information management in facilities management and maintenance is still challenged by the lack of a structured framework that can simultaneously fulfil these three capabilities: (1) the delivery of information models (i.e. Asset Information Models) from distributed data sources; (2) the validation of these information models against the requirements; and (3) the use of their information in facilities management (e.g. operation and maintenance). This research aims to develop and test a framework and a prototype Common Data Environment (CDE) to achieve these three capabilities.The framework and the developed CDE are entirely based on use open standards and integration of existing technologies. A requirements model, underpinning the framework and the CDE was developed during three iterative stages of interviews -in line with the adopted Grounded Theory and Design Science Research methodologies -with industry experts and through a three-stage coding process at each iteration. The framework and the CDE were tested in pilot demonstrations with a use case focused on preventive and reactive maintenance. The testing demonstrated that the implementation of 'BIM for FM' processes is feasible with the proposed framework and CDE using only open standards and existing technologies. Some additional requirements for BIM for FM processes were also identified during the verification sessions with industry and are proposed for future research.

Health and safety (H&S) is a major concern in the construction industry. Recent and historical data from the construction industry worldwide demonstrate that the human, social, and economic burden, inflicted as a result of H&S fatalities, is still significant. Training is considered one of the main strategies to reduce H&S risks. In recent years, the use of serious games for H&S training in construction has emerged in an attempt to overcome issues associated with traditional training methods.Current research in serious games has mainly focussed on scenario-led training where trainees interact with the same environment through a pre-selected number of options in discrete sections. This approach has limitations in terms of variety and amount of skills that trainees perceive from the game. In this paper, an approach that combines serious games design with 4D (3D + time) modelling is presented and tested in terms of its influence on increasing the capability of labourers to spot hazards at different time periods during the construction process, providing them with increased immersion in the virtual training environment. The results demonstrated that a combination of serious games and 4D approaches can improve users' engagement and affect their abilities to spot H&S hazards.

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The issue of interoperability in the Architecture, Engineering, and Construction (AEC) industry represents a challenge on a scale that spans across the project life cycle. This is predominant in the infrastructure sector that usually comprises a more versatile Operations and Maintenance (O&M) phase in comparison with the buildings sector. To this end, an important stage in the information life cycle is the asset information capture and validation during product procurement at the O&M phase. The water industry in the United Kingdom relies on Product Data Templates (PDTs) to fulfil such task, which is usually an error prone manual process. This paper presents an ongoing research, which investigates the application of Semantic Web Technologies (SWT) for improving product data exchange during product procurement at the O&M phase for the water industry in the United Kingdom (UK). Therefore, focus group sessions with industry experts were held to discuss current inefficiencies and solution requirements. Based on these results, a semantic common model named Asset Specification Ontology (ASO) was developed to capture and validate asset information during product procurement at the O&M phase. The common model (ontology) is based on available technologies, namely Web Ontology Language (OWL) and Shapes Constraint Language (SHACL). This gives the advantage of semantically rich data which can be linked and queried in a meaningful way to facilitate the exchange and validation of water industry assets’ data. The uniqueness of this paper is manifested in the issue it tackles, as efficient product procurement, and hence, data exchange in the water industry is an industrial challenge that is seldom researched. Results from the focus group sessions showed that information exchange within the UK water industry is impeded due to the lack of structured and semantic data. However, for a robust semantic interoperability, there needs to be a robust semantic data infrastructure, which would require semantic mappings from standards to product properties, from standards to other standards, and from standards to dictionaries. These conclusions were further supported by the common model, which was created from existing schemas, standards, and dictionaries. Generally, this paper recommends a common model/product library for phase-specific product data exchange in the water industry.