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When BIM Meets MBSE: Building a Semantic Bridge for Infrastructure Data Integration

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Publicado en:Systems vol. 13, no. 9 (2025), p. 770-795
Autor principal: Murphy, Joseph
Otros Autores: Ji Siyuan, Dickerson, Charles, Goodier, Chris, Zahiroddiny Sonia, Thorpe, Tony
Publicado:
MDPI AG
Materias:
National Aeronautics & Space Administration > NASA
United Kingdom > UK
Linked Data
Data exchange
Model-based systems
Industry 4.0
Productivity
Railway stations
Architecture
Aerospace industry
Data integration
Semantic web
Aerospace engineering
Research & development > R&D
Decision making
Infrastructure
High speed rail
Systems engineering
Construction
Semantics
Digital twins
Structured data
Industrial applications
Sustainable development
Unstructured data
Real time
Building information modeling
Information management
Acceso en línea:Citation/Abstract
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Resumen:The global infrastructure industry is faced with increasing system complexity and requirements driven by the Sustainable Development Goals, technological advancements, and the shift from Industry 4.0 to human-centric 5.0 principles. Coupled with persistent infrastructure investment deficits, these pressures necessitate improved methods for efficient requirements management and validation. While digital twins promise transformative real-time decision-making, reliance on static unstructured data formats inhibits progress. This paper presents a novel framework that integrates Building Information Modelling (BIM) and Model-Based Systems Engineering (MBSE), using Linked Data principles to preserve semantic meaning during information exchange between physical abstractions and requirements. The proposed approach automates a step of compliance validation against regulatory standards explored through a case study, utilising requirements from a high-speed railway station fire safety system and a modified duplex apartment digital model. The workflow (i) digitises static documents into machine-readable MBSE formats, (ii) integrates structured data into dynamic digital models, and (iii) creates foundations for data exchange to enable compliance validation. These findings highlight the framework’s ability to enhance traceability, bridge static and dynamic data gaps, and provide decision-making support in digital twin environments. This study advances the application of Linked Data in infrastructure, enabling broader integration of ontologies required for dynamic decision-making trade-offs.
ISSN:2079-8954
DOI:10.3390/systems13090770
Fuente:Advanced Technologies & Aerospace Database