In the age of virtualization, rapid urbanization and fierce competition, more and more “digital twins” of real cities are being created as a time, cost-efficient and especially user-oriented solution to many problems in urban planning and management. One prominent task is to efficiently detect progresses made by a city based on their virtual 3D city models recorded over the years, and then interpret them accordingly with respect to different groups of users and stakeholders involved in the process. The first half of the problem, namely automated change detection in city models, has been addressed in recent studies. The other half of the problem however, namely a user-oriented interpretation of detected changes, still remains. Thus, based on the current findings, this research extends the conceptual models and definition of different types of edit operations between city models using a graph database, where the graph representations of city models are also stored. New rules and conditions are then provided to further categorize these changes based on their semantic contents. Considering the different expectations and requirements of different groups of users and stakeholders, the research aims to provide a multi-perspective interpretation of such categorized changes.