Semantic digital twins for masonry bridges: Structuring geometrical, material and assessment field data

This paper addresses the integration of geometric and material data from masonry bridges within digital twins prepared to be part of bridge management systems. The study proposes a prototypical knowledge graph–based digital twin system focused on semantic interoperability to structure this data. The system supports storage, inspection and evaluation of masonry bridges. Different digitization strategies are encompassed together in an open, knowledge graph-based system. Information flows is exemplified from data collection to decision-making indicators. For the former, material charaterization and scan-to-BIM techniques exemplify data gathering. For the latter, the Masonry Quality Index (MQI) is used as an exemplary guide and indicator asset assessment. An open, dynamic representation of the asset can serve as a reference data structure for infrastructure managers—capable not only of aggregating but also of contextualizing diverse and critical streams of asset information, thereby transforming fragmented data into actionable intelligence. A user interface, conceived simultaneously under user-centered and developer-centered perspectives, is also presented. • Propose a knowledge graph-based digital twin system for masonry bridges. • Integrate BIM geometries with storage, inspection, an assessment capabilities. • Apply the Masonry Quality Index (MQI) as a performance indfor asset- and network-level decisions. • Enable open, realistic representations that turn fragmented data into actionable insights. • Present a dual-perspective user interface for managers and developers alike.

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Publication Details

Journal
Engineering Structures
Published
2026-03-12
DOI
https://doi.org/10.1016/j.engstruct.2026.122503
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
0.00
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article

Semantic digital twins for masonry bridges: Structuring geometrical, material and assessment field data

R. Chacón, Hector Posada, Marc Ventosa San Martino, Carlos Ramonell
Engineering Structures
3D Surveying and Cultural Heritage
article

Semantic digital twins for masonry bridges: Structuring geometrical, material and assessment field data

R. Chacón, Hector Posada, Marc Ventosa San Martino, Carlos Ramonell
article en

Abstract

This paper addresses the integration of geometric and material data from masonry bridges within digital twins prepared to be part of bridge management systems. The study proposes a prototypical knowledge graph–based digital twin system focused on semantic interoperability to structure this data. The system supports storage, inspection and evaluation of masonry bridges. Different digitization strategies are encompassed together in an open, knowledge graph-based system. Information flows is exemplified from data collection to decision-making indicators. For the former, material charaterization and scan-to-BIM techniques exemplify data gathering. For the latter, the Masonry Quality Index (MQI) is used as an exemplary guide and indicator asset assessment. An open, dynamic representation of the asset can serve as a reference data structure for infrastructure managers—capable not only of aggregating but also of contextualizing diverse and critical streams of asset information, thereby transforming fragmented data into actionable intelligence. A user interface, conceived simultaneously under user-centered and developer-centered perspectives, is also presented. • Propose a knowledge graph-based digital twin system for masonry bridges. • Integrate BIM geometries with storage, inspection, an assessment capabilities. • Apply the Masonry Quality Index (MQI) as a performance indfor asset- and network-level decisions. • Enable open, realistic representations that turn fragmented data into actionable insights. • Present a dual-perspective user interface for managers and developers alike.

Engineering StructuresVol. 357
Universitat Politècnica de Catalunya (ES)
Sustainable cities and communities
Openalex Percentile: Top 32%
3D Surveying and Cultural Heritage
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