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.

中文翻译：

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用于监控施工工作流程的语义数字孪生框架

随着施工工作流变得越来越动态，对数字孪生 （DT） 的支持集成、实时工作流监控的需求越来越大。然而，由于数据源分散和缺乏系统的语义集成方法，在构建中建立 DT 仍然具有挑战性。本文研究了如何系统地应用语义 Web 本体来建立用于监控施工工作流程的语义 DT。因此，提出了一个 DT 框架 （DiCon-DT），利用本体网络对各种数据进行建模并将其集成到语义 DT 数据湖中，并进一步实现仿真和上下文解释。通过家具安装案例研究的验证，该框架成功实现了语义数据集成，并支持施工监控的预测和认知任务。未来的研究应侧重于扩展本体网络、自动化语义数据映射以及在更大的复杂项目规模上验证框架。