The construction industry is characterized by fragmented information flows, where tasks, costs, resources, and BIM-based building objects are typi-cally managed using separate and unconnected tools and documents. This frag-mentation prevents cross-domain consistency checks and undermines effective project control. To address this challenge, the paper proposes a semantic meth-odology that integrates heterogeneous construction data using ontologies, RDF, and SPARQL querying. This approach translates conventional project docu-ments, such as IFC models, cost items, and scheduling time schedules, into an RDF knowledge graph structured according to domain-specific ontologies. A suite of standardized SPARQL queries facilitates the evaluation of cross-domain consistency between the data. The results are visualized via an interac-tive dashboard, providing decision support for project managers, including those without specialized expertise. The methodology has been validated through a real-world case study. The findings underscore the potential of se-mantic technologies to identify misalignments, reduce data silos, and enhance transparency, traceability, and coordination throughout the project lifecycle. This proposed system illustrates how semantic interoperability and Linked Data principles can improve project management practices within the architecture, engineering, and construction sector.

Semantic Integration of Cost, Time, Resource, and Geometry for Data-Driven Construction Management: An Interactive Dashboard for Decision Support

J. Cassandro;C. Mirarchi
2026-01-01

Abstract

The construction industry is characterized by fragmented information flows, where tasks, costs, resources, and BIM-based building objects are typi-cally managed using separate and unconnected tools and documents. This frag-mentation prevents cross-domain consistency checks and undermines effective project control. To address this challenge, the paper proposes a semantic meth-odology that integrates heterogeneous construction data using ontologies, RDF, and SPARQL querying. This approach translates conventional project docu-ments, such as IFC models, cost items, and scheduling time schedules, into an RDF knowledge graph structured according to domain-specific ontologies. A suite of standardized SPARQL queries facilitates the evaluation of cross-domain consistency between the data. The results are visualized via an interac-tive dashboard, providing decision support for project managers, including those without specialized expertise. The methodology has been validated through a real-world case study. The findings underscore the potential of se-mantic technologies to identify misalignments, reduce data silos, and enhance transparency, traceability, and coordination throughout the project lifecycle. This proposed system illustrates how semantic interoperability and Linked Data principles can improve project management practices within the architecture, engineering, and construction sector.
2026
Proceedings of International Conference on Digital Frontiers in Buildings and Infrastructure (DFBI2025)
Linked Data
Cross-checking of construction domains
Decision-making support system
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1309636
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