A digital twin uses classification system for urban planning & city infrastructure management

Recently, the concept of Digital Twin [DT] has pervaded the field of urban planning and city infrastructure management. This paper first affirms that the knowledge created by virtue of DT real-world implementation, through undertaking various DT pilot projects, case studies and proof-of-concept initiatives, comprises the ‘know-how’ and genuine practical experience upon which the DT research and practices can further develop and mature. It then argues that this type of knowledge is poorly captured and mostly left neither realized nor fully utilized. This significantly hinders the rate by which DT practices within the urban and built environments evolve. While acknowledging the benefits of the ongoing work by many DT researchers, including enumeration, categorization and detailing of multiple DT use cases, such endeavours arguably suffer from three profound weaknesses causing the inefficient sharing and transfer of DT ‘know-how’ knowledge amongst DT stakeholders. The three limitations are: (a) lack of DT standard terminology constituting a common DT language; (b) lack of standard and clear methods to enable documenting DT projects and making the ‘know-how’ explicit to the rest of the DT market; and (c) the lack of an established and adequate DT use cases classifications system to guide DT practitioners in searching for and retrieving the previously accomplished DT case studies that are most relevant to their interests and context. Correspondingly, three solutions are proposed constituting a three-pronged DT Uses Classification System [DTUCS]: prong-A (i.e. Standardize-to-Publish); prong-B (i.e. Detail-to-Prove); and prong-C (i.e. Classify-to-Reach). DTUCS is developed using a meta-methodology encapsulating a systematic literature review and three distinct sub-methodologies. The paper concludes with an overview of the implications of DTUCS along with recommendations on how it can be further validated and improved.