Dynamic Multi-Model Container Framework for Cloud-Based Distributed Digital Twins (dDTws)
The increasing complexity of data management in the Architecture, Engineering, and Construction (AEC) industry, driven by the adoption of distributed digital twins (dDTws) and cloud-based solutions, presents challenges in interoperability, data sovereignty, and scalability. Existing Building Informa...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Buildings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-5309/15/10/1722 |
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| Summary: | The increasing complexity of data management in the Architecture, Engineering, and Construction (AEC) industry, driven by the adoption of distributed digital twins (dDTws) and cloud-based solutions, presents challenges in interoperability, data sovereignty, and scalability. Existing Building Information Modeling (BIM) and Common Data Environment (CDE) frameworks often fall short in addressing these issues due to their reliance on centralized and proprietary systems. This paper introduces a novel framework that transforms the Information Container for Linked Document Delivery (ICDD) into a dynamic, graph-based architecture. Unlike conventional file-based ICDD implementations, this approach enables fine-grained, semantically rich linking and querying across distributed models while maintaining data sovereignty and version control. The framework is designed to enhance real-time collaboration, ensure secure and sovereign data management, and improve interoperability across diverse project stakeholders. The framework leverages graph databases, semantic web technologies, and ISO standards such as ISO 21597 to facilitate seamless data exchange, automated linking, and advanced version control. Key functionalities include federated data storage, compliance with local and international regulations, and support for multidisciplinary workflows in large-scale AEC projects. To demonstrate the feasibility of the proposed framework, a simplified use case scenario is implemented and analyzed. By addressing critical challenges and enabling seamless integration of emerging technologies such as digital twins, this study advances the state of the art in data management for the AEC industry, providing a robust foundation for future innovations. |
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| ISSN: | 2075-5309 |