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Top1. Introduction
While every industry is thinking about reshaping their business to thrive in the post-COVID-19 era, the architecture, engineering, construction, and operation (AECO) industry is emerging the Digital Twin (DT) initiative to build a new more intelligent, more productive, and safer built environment. This initiative is aligned with Industry 4.0 to advance new practices and tools to overcome the legacy associated with saying “BIM” for almost a decade. A DT refers to a digital replica of physical assets, processes, and systems (Lu et al., 2020a). This twin would enable the AECO sector to collaborate virtually, present sensor data, simulate conditions quickly, realise outputs of the what-if scenarios undoubtedly, predict results more accurately, and provide instructions to manage the physical world more effectively. Grieves and Vickers (2017) argued that DT's rationality definition is to have just the efficient data without intensively using resources, in other words, an integration between dynamic modelling with real-time optimisation through the whole lifecycle. Building information modelling (BIM), according to the ISO 19650 series, “is about getting benefit through better specification and delivery of just the right amount of information concerning the design, construction, operation, and maintenance of buildings and infrastructure, using appropriate technologies”. BIM is, to an extent, seen as an analogue to DT in the AECO sector. For this paper's argument, the authors identify BIM as an environment where processes, technologies, and resources are integrated for better delivery. In contrast, DT is an advanced deliverable of this integrated environment. In this analogy, both BIM nowadays deliveries for AM and DT have one main challenge hindering their adoption: data interoperability (Matarneh et al., 2019b). That challenge is the critical barrier to overcome, as the entire theoretical framework of any information management technology is predicated on the assumption that data can be exchanged simultaneously between software programs (Farghaly et al., 2018).
Data interoperability is the ability that all other parties can correctly interpret data generated by any one party. Also, it enhances the data exchange between two or more diverse systems to facilitate automation and avoidance of data re-entry (Shen et al., 2010). To achieve effective data exchange between applications, the proposed solution should achieve both semantic and syntactic interoperability (Farghaly et al., 2019). Syntactic interoperability solutions identify an agreed exchange format to transfer data, and semantic interoperability solutions identify a set of terms and data requirements to enable interoperation using the agreed exchange format defined by syntactic interoperability. Several works were conducted to achieve both semantic and syntactic interoperability between BIM and AM platforms, with more concentration on syntactic interoperability (Cavka et al., 2017). Despite all the efforts and contributions, the construction industry's available solutions for interoperability are still insufficient to leverage DT's potential (Sacks et al., 2020). A comprehensive review of previous research can provide significant benefits in identifying areas where additional research work is required, and in the process, discerning future directions for the development of the effective interoperability environment of the DT initiative.