<p>Data operation and maintenance in station-city integrated cyberspace represent a cross-domain application scenario that spans smart transportation and smart cities. This scenario involves multi-source heterogeneous data from diverse contexts, including sensor-collected data, Building Information Modeling (BIM), and City Information Modeling (CIM). However, challenges remain in managing massive multi-source heterogeneous data storage, eliminating information silos, and enhancing data fusion efficiency within such integrated frameworks. To address these challenges, this study proposes a Data Lakehouse architecture tailored for the intelligent operation and maintenance of Shenzhen North Railway Station’s station-city integrated cyberspace. Additionally, this paper defines domain-specific storage and query meta-models for five critical operation and maintenance scenarios: structure, environment, human flow, events, and energy consumption. By integrating ubiquitous multi-dimensional state perception, intelligent evaluation, and emergency response simulations, it ensures data-driven implementation of intelligent operation and maintenance systems for station-city integrated cyberspace.</p>