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Article

Federated Data Modelling for Heritage Building Performance Management

1
Department of Architecture, University of Bologna, 40136 Bologna, Italy
2
Department of Engineering and Applied Sciences, University of Bergamo, 24044 Dalmine, Italy
3
Energy Efficiency Unit Department, Italian National Agency for New Technologies, Energy and Sustainable Economic Development, 00123 Rome, Italy
4
Energy Efficiency Unit Department, Italian National Agency for New Technologies, Energy and Sustainable Economic Development, 06124 Perugia, Italy
*
Author to whom correspondence should be addressed.
Buildings 2026, 16(1), 27; https://doi.org/10.3390/buildings16010027 (registering DOI)
Submission received: 29 September 2025 / Revised: 9 December 2025 / Accepted: 17 December 2025 / Published: 20 December 2025

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).
Keywords: built heritage; building performance; decision support systems; building information modelling; knowledge graphs; digital twins built heritage; building performance; decision support systems; building information modelling; knowledge graphs; digital twins

Share and Cite

MDPI and ACS Style

Massafra, A.; Coraglia, U.M.; Di Turi, S.; Palladino, D. Federated Data Modelling for Heritage Building Performance Management. Buildings 2026, 16, 27. https://doi.org/10.3390/buildings16010027

AMA Style

Massafra A, Coraglia UM, Di Turi S, Palladino D. Federated Data Modelling for Heritage Building Performance Management. Buildings. 2026; 16(1):27. https://doi.org/10.3390/buildings16010027

Chicago/Turabian Style

Massafra, Angelo, Ugo Maria Coraglia, Silvia Di Turi, and Domenico Palladino. 2026. "Federated Data Modelling for Heritage Building Performance Management" Buildings 16, no. 1: 27. https://doi.org/10.3390/buildings16010027

APA Style

Massafra, A., Coraglia, U. M., Di Turi, S., & Palladino, D. (2026). Federated Data Modelling for Heritage Building Performance Management. Buildings, 16(1), 27. https://doi.org/10.3390/buildings16010027

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