Federated Data Modelling for Heritage Building Performance Management

Abstract

The fragmentation of knowledge across multiple sources and players, coupled with limited access to information, is one of the main challenges for the performance-based management of heritage buildings. Despite recent research efforts in the field of Heritage Building Information Modelling (HBIM), this technology alone is insufficient for managing the variety of data related to building performance and is challenging for stakeholders without digital expertise to adopt. These limitations, along with advancements in knowledge technologies, have led to the emergence of federated data modelling approaches as a core strategy for managing the complexity of buildings’ operational information. To address data fragmentation, this research proposes a methodology for linking heterogeneous data on historic building performance. The approach structures heterogeneous data, gathered from multiple sources—HBIM models, sensors, and energy bills—into knowledge graphs that enable semantic integration, cross-domain queries and support interactive visualisation. As part of the BeTwin research project, the methodology is validated through its application to a case study in the Appia Antica Archaeological Park (Rome, Italy).