Semantic digital twin framework for monitoring construction workflows

As construction workflows become increasingly dynamic, there is a growing need for Digital Twins (DTs) to support integrated, real-time workflow monitoring. However, establishing DTs in construction remains challenging due to fragmented data sources and the lack of systematic semantic integration methods. This paper investigates how semantic web ontologies can be systematically applied to establish a semantic DT for monitoring construction workflows. Accordingly, a DT framework (DiCon-DT) is proposed, utilizing an ontology network to model and integrate diverse data into a semantic DT data lake, and further enabling simulation and contextual interpretation. Validated through a furniture installation case study, the framework successfully enabled semantic data integration and supported predictive and cognitive tasks for construction monitoring. Future research should focus on extending the ontology network, automating semantic data mapping, and validating the framework at larger complex project scales.