## 1 Introduction
The research methodology of this study is based on a systematic literature review of 210 relevant articles based on digital twins and smart cities from 2011 to 2022. The researchers highlight digital twins' potential to address various issues at the city level by actively involving citizens in infrastructure governance. The researchers emphasize that although most of the projects use data from open-source data platforms, data derived from volunteered geographic information and social sensing are two prominent methods for central digital twin platforms. The researchers propose machine learning classifiers for digital twin capabilities, such as incorporating sparse data and using change detection algorithms for infrastructure dispersion analysis. The study also identifies application processing interfaces for CCDT that facilitate interactive visualization for informed decision-making during citizen participation in infrastructure governance. CesiumIS is highlighted as a significant API, particularly in digital city twin applications in capital cities like Victoria and Sydney. However, it is a commercial platform, and the free version is only for personal and not public projects, exploratory development, or educational activities. Ref. [9] highlights the growing interest in digital twins in urban and geospatial domains, particularly at the city-scale level. The study aims to bridge the gap between conceptual understanding and current realizations of digital twins for cities by analyzing the literature and survey results. The study collects and refines definitions of digital twins for cities from a corpus of 26 papers, focusing on computer science, urban planning, and city-level geospatial fields. A key finding underscores the importance of clearly defining concepts and approaches to understand the practical input layer of digital twins for cities. Current implementations often confuse the concept with other notions, sometimes treating it as a technological evolution of 3D urban modeling. The study suggests that considering digital twins for cities as systems of systems is a prominent approach, with 15 papers defining it as a digital representation of city elements functioning as an ecosystem of twin systems without limiting the scope to 3D components. The analysis reveals that the city information model (CIM) is primarily regarded as the input layer of digital twins for cities. Additionally, the establishment of spatial data infrastructure (SDI) is considered crucial for creating a robust geospatial digital twin, serving as the cornerstone for ensuring seamless access to the data hub and efficient, standardized data integration. Through an in-depth examination of 184 pertinent articles that were carefully selected and analyzed, Ref. [10] synthesizes the various disciplinary classifications associated with the functional integration of geographic information systems (GIS) and building information models (BIMs). The study distills the importance of data and argues that while smart city platform application cases have taken initial steps to achieve analytical computing through GIS and BIM techniques, ongoing research is dedicated to improving interoperability. The researchers stress that the improvement of interoperability in digital twin technology, coupled with the integration of richer data formats and factoring in the importance of time management cycles, is key to developing a more coherent system of smart city applications. Therefore, this holistic approach not only streamlines the processes but also helps to reduce the corresponding costs throughout the life cycle of a smart city project by seamlessly transitioning through various stages, spanning from surveying, planning, and design to construction, operation, and maintenance. The researchers in Ref. [11] highlight the evolving role of the digital twin concept in extracting value from data and its increasing importance in designing and managing diverse systems.