Semantic Digital Twins in Construction: Developing a modular System Reference Architecture based on Information Containers

The construction industry is increasingly adopting Digital Twin (DT) technology to support the design, construction, and operation of buildings and structures. In this context, a key challenge for DTs is integrating heterogeneous data sources to address requirements that evolve across different life cycle phases and use cases. A modular approach for deploying DTs offers a flexible and scalable solution that can adapt to these changing requirements. However, a clear definition and structure of DT modules for the built environment are still missing. This research presents a modular System Reference Architecture (SRA) for implementing Semantic DTs in the construction industry. As its central component, the SRA leverages the inherently modular Asset Administration Shell (AAS) reference model for asset DTs in Industry 4.0. Built on submodels, each addressing a specific use case or aspect, the AAS serves as a high-level framework for DTs. The SRA extends the AAS with standardized Information Containers for Linked Document Delivery (ICDD), integrated through a Linked Data approach employing a semantic layer of ontologies. The feasibility of the proposed SRA is demonstrated through a case-specific implementation for the precast concrete production. Two submodels are developed within the SRA: one for accessing dynamic sensor data via time series databases and another for integrating BIM-derived semantic data using ICDD. The architecture is evaluated through a simulated curing process, where SPARQL and REST-based queries enable real-time monitoring and feedback control. The results confirm the SRA’s ability to integrate heterogeneous data sources, support semantic interoperability, and facilitate lifecycle-oriented feedback mechanisms.