The Development and Construction of City Information Modeling (CIM): A Survey from Data Perspective †

Abstract

With rapid urbanization exacerbating the challenges in resource allocation, environmental sustainability, and infrastructure management, City Information Modeling (CIM) has emerged as an indispensable digital solution for smart city development. CIM represents an advanced urban management paradigm that integrates Geographic Information Systems (GISs), Building Information Modeling (BIM), and the Internet of Things (IoT) to establish a multidimensional digital framework for comprehensive urban data management and intelligent decision making. While the existing research has primarily focused on technical architectures, governance models, and application scenarios, a systematic exploration of CIM’s data-driven characteristics remains limited. This paper reviews the evolution of CIM from a data-centric view introducing a research framework that systematically examines the data lifecycle, including acquisition, processing, analysis, and decision support. Furthermore, it explores the application of CIM in key areas such as smart transportation and digital twin cities, emphasizing its deep integration with big data, artificial intelligence (AI), and cloud computing to enhance urban governance and intelligent services. Despite its advancements, CIM faces critical challenges, including data security, privacy protection, and cross-sectoral data sharing. This survey highlights these limitations and points out the future research directions, including adaptive data infrastructure, ethical frameworks for urban data governance, intelligent decision-making systems leveraging multi-source heterogeneous data, and the integration of CIM with emerging technologies such as AI and blockchain. These innovations will enhance CIM’s capacity to support intelligent, resilient, and sustainable urban development. By establishing a theoretical foundation for CIM as a data-intensive framework, this survey provides valuable insights and forward-looking guidance for its continued research and practical implementation.