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Book Chapter

Semantic Web Based Integration Between BIM Cost and Geometric Domains

  • Jacopo Cassandro
  • Claudio Mirarchi
  • Alberto Pavan
  • Andrea Zamborlini

In the architecture, engineering, construction, and facilities management (AEC/FM) industry methodologies are needed to ensure the interoperability of data and effective management of information from different sources. Integration of the cost domain and cost estimation within the Building Information Model (BIM) in the AEC/FM sector is still an unresolved problem and one of the most critical tasks due to the lack of a standardised cost domain, especially in the tendering phase. To ensure interoperability between cost data and geometric data, this research aims to address this gap by analyzing methods of converting cost data into Linked Building Data, thereby defining a cost domain in the Semantic Web, by collecting them into a graph database. This allows for structuring a cost domain, translating an IFC based structure previously developed by the research group, visualizing it using a graph system, and connecting it to the BIM geometric domain. Furthermore, it is possible to extend the cost ontology previously identified in the IFC model and facilitate the queries and analysis of cost data currently fragmented and based on unstructured data. The results show how Semantic Web technology can be used to improve data interoperability, develop a cost ontology, and join both cost data and BIM models

  • Keywords:
  • Semantic Web,
  • Linked Building Data,
  • IfcOWL,
  • cost ontology,
  • IFC,
  • RDF,
  • graph system,
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Jacopo Cassandro

Politecnico di Milano, Italy - ORCID: 0000-0002-1487-8178

Claudio Mirarchi

Politecnico di Milano, Italy - ORCID: 0000-0002-9288-8662

Alberto Pavan

Politecnico di Milano, Italy - ORCID: 0000-0003-0884-4075

Andrea Zamborlini

University of Padua, Italy


University of Padua, Italy - ORCID: 0000-0002-8185-4301

  1. Abanda, F. H., Tah, J. H. M., Pettang, C., & Manjia, M. B. (2011). An ontology-driven building construction labour cost estimation in Cameroon. Electronic Journal of Information Technology in Construction, 16(January), 617–634.
  2. Abanda, H., Ng’Ombe, A., Tah, J. H. M., & Keivani, R. (2011). An ontology-driven decision support system for land delivery in Zambia. Expert Systems with Applications, 38(9), 10896–10905. DOI: 10.1016/j.eswa.2011.02.130
  3. Beetz, J., Coebergh Van Den Braak, W., Botter Eindhoven, R., Zlatanova, S., & De Laat, R. (2015). Interoperable data models for infrastructural artefacts - A novel IFC extension method using RDF vocabularies exemplified with quay wall structures for harbors. EWork and EBusiness in Architecture, Engineering and Construction - Proceedings of the 10th European Conference on Product and Process Modelling, ECPPM 2014, 135–140. DOI: 10.1201/B17396-26
  4. Beetz, J., Van Leeuwen, J., & De Vries, B. (2009). IfcOWL: A case of transforming EXPRESS schemas into ontologies. Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM, 23(1), 89–101. DOI: 10.1017/S0890060409000122
  5. Beetz, J., van Leeuwen, J. P., & de Vries, B. (2005). An Ontology Web Language Notation of the Industry Foundation Classes. Proceedings of the 22nd CIB W78 Conference on Information Technology in Construction, January 2005, 193–198.
  6. Berners-Lee, T., Hendler, J., & Lassila, O. (2001). THE SEMANTIC WEB. Scientific American, 284(5), 34–43.
  7. Bonduel, M., Oraskari, J., Pauwels, P., Vergauwen, M., & Klein, R. (2018). The IFC to linked building data converter - Current status. CEUR Workshop Proceedings, 34–43.
  8. BuildingSMART. (2022). IfcCostItem. IFC4_ADD2_TC1 - [Official].
  9. Cassandro, J., Donatiello, M. G., Mirarchi, C., Zanchetta, C., & Pavan, A. (2023). Reliability of IFC classes in ontology definition and cost estimation of public procurement. 2023 European Conference on Computing in Construction 40th International CIB W78 Conference Heraklion, Crete, Greece.
  10. Curry, E., O’Donnell, J., Corry, E., Hasan, S., Keane, M., & O’Riain, S. (2013). Linking building data in the cloud: Integrating cross-domain building data using linked data. Advanced Engineering Informatics, 27(2), 206–219. DOI: 10.1016/J.AEI.2012.10.003
  11. Fürstenberg, D., Wikström, L., Laedre, O., & No, O. L. (2021). Enabling automation of BIM-based cost estimation by semantic web technology. ITC Digital Library, 937–945.
  12. Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2), 199–220.
  13. Hoang, N. V., & Torma, S. (2015). Implementation and Experiments with an IFC-to-Linked Data Converter. Proc. of the 32nd CIB W78 Conference 2015, 27th-29th October 2015, Eindhoven, The Netherlands, 1, 285–294.
  14. ifcOWL - buildingSMART Technical. (2023). Retrieved June 23, 2023, from
  15. Ismail, A., Nahar, A., & Scherer, R. (2017). Application of graph databases and graph theory concepts for advanced analysing of BIM models based on IFC standard. Digital Proceedings of the 24th EG-ICE International Workshop on Intelligent Computing in Engineering 2017, July, 146–157.
  16. Jung, S., Lee, S., & Yu, J. (2021). Ontological approach for automatic inference of concrete crack cause. Applied Sciences (Switzerland), 11(1), 1–20. DOI: 10.3390/app11010252
  17. Karan, E., Irizarry, J., & Haymaker, J. (2015). Generating IFC models from heterogeneous data using semantic web. Construction Innovation, 15(2), 219–235. DOI: 10.1108/CI-05-2014-0030
  18. Krijnen, T., & Beetz, J. (2018). A SPARQL query engine for binary-formatted IFC building models. Automation in Construction, 95, 46–63. DOI: 10.1016/J.AUTCON.2018.07.014
  19. Malcolm, A., Werbrouck, J., & Pauwels, P. (2021). LBD Server: Visualising Building Graphs in Web-Based Environments Using Semantic Graphs and GlTF-Models. Advances in Science, Technology and Innovation, 287–293. DOI: 10.1007/978-3-030-57509-0_26
  20. Malinverni, E. S., Naticchia, B., Lerma Garcia, J. L., Gorreja, A., Lopez Uriarte, J., & Di Stefano, F. (2022). A semantic graph database for the interoperability of 3D GIS data. Applied Geomatics, 14, 53–66. DOI: 10.1007/s12518-020-00334-3
  21. Mazairac, W., & Beetz, J. (2013). BIMQL – An open query language for building information models. Advanced Engineering Informatics, 27(4), 444–456. DOI: 10.1016/J.AEI.2013.06.001
  22. OWL - Semantic Web Standards. (2023). Retrieved June 23, 2023, from
  23. Pauwels, P., & Deursen, D. Van. (2015). IFC-to-RDF : Adaptation , Aggregation and Enrichment IFC / RDF : Adaptation , Aggregation and Enrichment. October, 2–5.
  24. Pauwels, P., Krijnen, T., Terkaj, W., & Beetz, J. (2017). Enhancing the ifcOWL ontology with an alternative representation for geometric data. Automation in Construction, 80, 77–94. DOI: 10.1016/j.autcon.2017.03.001
  25. Pauwels, P., & Terkaj, W. (2016). EXPRESS to OWL for construction industry: Towards a recommendable and usable ifcOWL ontology. Automation in Construction, 63, 100–133. DOI: 10.1016/j.autcon.2015.12.003
  26. Pauwels, P., Terkaj, W., Krijnen, T., & Beetz, J. (2015). Coping with lists in the ifcOWL ontology. EG-ICE 2015 - 22nd Workshop of the European Group of Intelligent Computing in Engineering.
  27. Pauwels, P., Zhang, S., & Lee, Y. C. (2017). Semantic web technologies in AEC industry: A literature overview. Automation in Construction, 73, 145–165.
  28. Pérez, J., Arenas, M., & Gutierrez, C. (2010). nSPARQL: A navigational language for RDF. Journal of Web Semantics, 8(4), 255–270. DOI: 10.1016/J.WEBSEM.2010.01.002
  29. Rasmussen, M. H., Pauwels, P., Lefrançois, M., Schneider, G. F., Hviid, C. A., & Karlshøj, J. (2017). Recent changes in the Building Topology Ontology.
  30. Rodriguez, M. A., & Neubauer, P. (2010). Constructions from dots and lines. Bulletin of the American Society for Information Science and Technology, 36(6), 35–41. DOI: 10.1002/BULT.2010.1720360610
  31. Silvescu, A., & Caragea, D. (2019). Graph Databases. Computer Science - Encyclopedia of Big Data Technologies, 835–835.
  32. The Linked Building Data Community Group. (2021).
  33. Vakaj, E., Lecturer, S., Environment, B., Cheung, F., Environment, B., Cao, J., Management, I., Tawil, A. H., Environment, B., Patlakas, P., & Environment, B. (2023). An ontology-based cost estimation for offsite construction. 28(March), 220–245. DOI: 10.36680/j.itcon.2023.011
  34. Zhang, S., Boukamp, F., & Teizer, J. (2015). Ontology-based semantic modeling of construction safety knowledge: Towards automated safety planning for job hazard analysis (JHA). Automation in Construction, 52, 29–41. DOI: 10.1016/j.autcon.2015.02.005
  35. Zhao, Q., Li, Y., Hei, X., & Yang, M. (2020). A Graph-Based Method for IFC Data Merging. Advances in Civil Engineering, 2020. DOI: 10.1155/2020/8782740
  36. Zhu, J., Chong, H., Zhao, H., Wu, J., & Tan, Y. (2022). The Application of Graph in BIM / GIS Integration.
  • Publication Year: 2023
  • Pages: 813-823

  • Publication Year: 2023

Chapter Information

Chapter Title

Semantic Web Based Integration Between BIM Cost and Geometric Domains


Jacopo Cassandro, Claudio Mirarchi, Alberto Pavan, Andrea Zamborlini, CARLO ZANCHETTA



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© 2023 Author(s)

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CC BY-NC 4.0

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CC0 1.0

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Book Title

CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality

Book Subtitle

Managing the Digital Transformation of Construction Industry


Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi

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© 2023 Author(s)

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CC BY-NC 4.0

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CC0 1.0

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Firenze University Press



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