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

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.

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Publication Details

Journal
Virtual Community of Pathological Anatomy (University of Castilla La Mancha)
Published
2026-01-01
Primary Topic
BIM and Construction Integration
Type
article
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article

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

C. Mirarchi, J. Cassandro
Virtual Community of Pathological Anatomy (University of Castilla La Mancha)
BIM and Construction Integration
article

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

C. Mirarchi, J. Cassandro
article en

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.

Virtual Community of Pathological Anatomy (University of Castilla La Mancha)
Industry, innovation and infrastructure
Openalex Percentile: Top 8%
BIM and Construction Integration
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Semantic Integration of Cost, Time, Resource, and Geometry for Data-Driven Construction Management: An Interactive Dashboard for Decision Support — C. Mirarchi, J. Cassandro · Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (2026) | TGRS Research Map | TGRS