City Information Modeling (CIM) is a research theme that builds on the principles of Building Information Modeling (BIM) and extends them to the urban scale. While BIM focuses on the digital representation of the physical and functional characteristics of a building or infrastructure project, CIM focuses on the digital representation of the physical, functional, and spatial characteristics of a city or urban area. CIM enables the integration of data and information from various sources, such as buildings, infrastructure, transportation, and environment, throughout the city life cycle. This provides a comprehensive and dynamic view of the city and its performance, which can support decision-making, planning, design, and management of cities and urban areas.

One of the key differences between BIM and CIM is the scale and complexity of the data and information that they handle. CIM involves managing and integrating large amounts of data and information from multiple sources, and this requires advanced data management and data governance capabilities. In CIM, the use of Relational Database Management Systems (RDBMS) and Geographic Information Systems (GIS) are crucial for data management and analysis. Furthermore, CIM also relies on parametric models, which allow for the creation of numerous variations of a design based on certain parameters such as site conditions, zoning laws, and building codes. These parametric models can provide a comprehensive and flexible approach to design, allowing for the exploration of different design options and the optimization of the design for different performance criteria.