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With extensive application of building information modeling (BIM), vast BIM model resources have accumulated from both new and existing projects. Digital twins, a key application of these models, face two main challenges: exponential growth in geometric and attribute data, risking data explosion, and low data utilization due to insufficient semantic association among multi-source data across projects and domains. This paper addresses the challenge of reducing system complexity via scenario-driven methods while achieving deep semantic integration of cross-domain BIM data. It proposes an ontology-based “Digital Theater” framework that defines data boundaries based on scenario requirements and employs dynamic trimming strategies to reduce complexity. By combining a simplified data standard with a multi-domain fusion ontology model, the framework constructs scenario-based data integration rules for semantic alignment. An adaptive relational database with object storage design further supports efficient engineering data storage and utilization. The proposed method significantly reduces the complexity of data processing, enabling the integrated application of multi-domain data at a lower cost while enhancing the decision-support capabilities of BIM data. This framework demonstrates potential for application in diverse scenarios, supporting engineering digitalization and smart city development.
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