BIM ONTOLOGY: TOWARD A COGNITIVE ARCHITECTURAL POLICY

Authors

  • José Luis Menegotto Author

DOI:

https://doi.org/10.56238/levv17n58-069

Keywords:

Open Linked Data, Semantic Web, Ontology, Regulatory Bodies

Abstract

The article describes the methodology for creating an ontology-building program in OWL. The system uses two main elements: Excel spreadsheets, which organize classes, properties, and test instances in a BIM domain, and a processing mechanism programmed in C# (Revit API 5.0). This mechanism reads the spreadsheets and generates OWL files in Manchester syntax and TTL turtle. The work revisits concepts from the 1980s and 1990s, highlighting the importance of ontologies for integrating BIM data into the Semantic Web, within the Open Linked Data paradigm. It advocates for the formulation of a cognitive architecture policy for processes, with regulatory bodies acting as centers for knowledge dissemination, suggesting a reformulation of the ways technical standards are published. Finally, in view of the advance of AI agents, the article reinforces the importance of investing in the structuring of factual knowledge.

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References

AASMAN, J. The foundation of data fabrics and AI: Semantic Knowledge Graph. Disponível em: https://www.datasciencecentral.com/the-foundation-of-data-fabrics-and-ai-semantic-knowledge-graphs/ May, 2022. Acesso em: abril de 2025.

AL-HAKAM, H.; SCHERER, R. J. Integration of BIM-related bridge information in an ontological knowledgebase. Conference: LDAC 2020 - 8th Linked Data in Architecture and Construction Workshop. 2020.

AISH, R. First Build Your Tools. Em: Inside SmartGeometry: Expanding the Architectural Possibilities of Computational Design. pp.36-49. Londres: Wiley. 2013.

BANG, Y.; CAHYAWIJAYA, S.; LEE, N.; DAI, W.; SU, D; WILIE, B.; LOVENIA, H.; JI, Z.; YU, T.; CHUNG, W.; DO, Q. V.; XU, Y; FUNG, P. A multitask, multilingual, multimodal evaluation of ChatGPT on reasoning, hallucination, and interactivity. ArXiv:2302.04023. 2023.

BIM4REN. D4.2 BIM4REN repository: software and user guide. Disponível em: https://bim4ren.eu/download/d4-2-bim4ren-repository-software-and-user-guide/ Acesso em: março de 2024

BORGO, S.; GALTON, A.; KUTZ, O. Foundational ontologies in action. understanding foundational ontology through examples. Applied ontology, v.17. n°1. pp.1–16. 2022. DOI: 10.3233/AO-220265

BEACH, T. H.; REZGUI, Y. Semantic Encoding of Construction Regulations. Proceedings of the 6th Linked Data in Architecture and Construction Workshop Londres, United Kingdom. 2018.

BEETZ, J.; LEEUWEN, J. V.; VRIES, B. IfcOWL: A case of transforming EXPRESS schemas into ontologies. Artificial Intelligence for Engineering Design, Analysis and Manufacturing. 2009. v.23, n.1, pp.89-101. DOI: https://doi.org/10.1017/S0890060409000122

BERNERS-LEE, T. Linked Data. 2009. Disponível em: https://www.w3.org/DesignIssues/LinkedData.html Acesso em: jul 2023.

BERNERS-LEE, T.; FIELDING, R.; MASINTER ,L. RFC 3986: Uniform Resource Identifier (URI): Generic Syntax. IETF Internet Engineering Task Force. 2005. Disponível em: http://www.ietf.org/rfc/rfc3986.txt Acesso em: jul 2023.

BFO. Basic Formal Ontology. 2020. Disponível em: https://basic-formal-ontology.org

BONDUEL, M.; ORASKARI, J.; PAUWELS, P.; VERFAUWEN, M.; KLEIN, R. The IFC to Linked Building Data Converter-Current Status. Em: Linked Data in Architecture and Construction Workshop 6. Londres. Proceedings […]. Londres: CEUR-WS. 2018. v.2159. pp.34-43. Acesso em: mai 25, 2019. Disponível em: http://ceur-ws.org/Vol-2159/

BRYANT, L. R. El principio óntico: boceto de una ontología orientada a objetos. FLORES PEÑA, G. R. (Tradução). Devenires , xviii , 35 (2017): 229-264. 2017.

bSDD. buildingSMART Data Dictionary. (2025). Disponível em: https://search.bsdd.buildingsmart.org/ Acesso em: mar 2025.

BUS, N.; ROXIN, A.; PICINBONO, G.; FAHAD, M. Towards French Smart Building Code: Compliance Checking Based on Semantic Rules Nicolas. Proceedings of the 6th Linked Data in Architecture and Construction Workshop. Londres, United Kingdom. 2018.

DEVEZAS, J.; NUNES, S. A Review of Graph Based Models for Entity Oriented Search. SN Computer Science. 2021. v.2, n.437 https://doi.org/10.1007/s42979-021-00828-w

ENGEL, H.; RAPSON, R. Tragsysteme. Hatje Cantz Verlag. 2007.

FIORAVANTI, A.; TRENTO, A. Close Future: Co-Design Assistant How Proactive design paradigm can help. Em: Proceedings of 37 eCAADe and XXIII SIGraDi Joint Conference, Architecture in the Age of the 4Th Industrial Revolution. SOUSA, J. P.; HENRIQUES, G. C.; XAVIER, J. P. (Eds.). São Paulo: Blucher. pp.155-162. DOI: 10.5151/proceedings-ecaadesigradi2019_516. 2019.

FLACH, P. Simply Logical. Intelligent Reasoning by Example. John Wiley, 1994.

FRANZ INC. (2025) Agentic AI with AllegroGraph’s Neuro-Symbolic Knowledge Graphs. White paper. In. Database. Trends and Application. March, 2025. Disponível em: https://allegrograph.com/wp-content/uploads/2025/03/Powering-GenAI-Apps with-Knowledge-Graphs-3-2025-2.pdf

GALKIN, M. Neural Graph Databases. A new milestone in graph data management. Disponível em: Towards Data Science. https://towardsdatascience.com/neural-graph-databases-cc35c9e1d04f, 2023. Acesso em: jan 2025.

GRUBER, T. R. Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies. v.43. pp.907-928. 1995. DOI: https://doi.org/10.1006/ijhc.1995.1081

HORRIDGE, M.; KNUBLAUCH, H.; RECTOR, A.; STEVENS, R.; WROE, C. A Practical Guide to building OWL ontologies using the Protégé-OWL plugin and CO-ODE Tools. Ed.1.0. The University of Manchester. 2004.

ISOTANI, S.; BITTENCOURT, I. I. Dados abertos conectados. São Paulo, Novatec Editora, 2015.

KASSEL, G. A plea for epistemic ontologies. Applied Ontology. v.18. n.4. pp.367 397. Dezembro 2023. DOI: 10.3233/AO-230031

LANDGREBE, J.; SMITH, B. Why Machines Will Never Rule the World. Artificial Intelligence without Fear. New York. Routledge. 2023.

LASKAR, T. R.; BARI. M. S.; RAHMAN, M.; BHUIYAN, A. H.; JOTY, S.; HUANG, J. A systematic study and comprehensive evaluation of ChatGPT on benchmark datasets. Em: Findings of the Association for Computational Linguistics: ACL 2023, pp. 431–469, Toronto, Canada. Association for Computational Linguistics. 2023. DOI: https://doi.org/10.48550/arXiv.2305.18486

LEVESQUE, H. J. Foundations of a functional approach to knowledge representation. Artificial Intelligence, v.23, pp.155-212. 1984.

MACIEL LIMA, J. P.; REIS PEREIRA, C. O princípio de não contradição: princípio ontológico, ôntico e gnosiológico do ser. The principle of non-contradiction: ontological, ontic and gnosiological principle of being. Revista Opinião Filosófica, v. 15, n. 2, e1078, p. 1-13, julho-dezembro, 2024 - ISSN: 2178-1176.

MENEGOTTO, J. L. O modelo digital. Técnica e arte algorítmica em BIM. Ed. Interciencia. Rio de Janeiro, 2023.

__________________ Ontologia BIM. Alguns Aspectos do Conhecimento Projetual: o Prédio, as IFC e as OST. Sigradi 2023. Accelerated Landscapes | Centro Universitario Regional Este (CURE) Facultad de Arquitectura, Diseño y Urbanismo | Universidad de la República. 2023.

__________________ The neuro symbolic AI: Formalize ontologies of BIM product catalogs. Sigradi 2025. Meta - Responsive Approaches faud. UNC. 2025.

MENGTIAN, Y.; LLELEWELLYN, T.; WEBSTER, C.; SHEN, X.; XIONGYI, L.; HUAQUAN, Y. An ontology-aided, natural language-based approach for multi-constraint BIM model querying. Journal of Building Engineering. n.76. Elsevier, 2023.

NEUHAUS, F. Ontologies in the era of large language models - a perspective. Applied Ontology. v.18. n.4. pp.399-407. Dezembro 2023. DOI: 10.3233/AO-230072

NEUHAUS, F.; GRENON, P.; SMITH, B. A Formal Theory of Substances, Qualities, and Universals. Em VARZI, A.; VIEU, L. (eds.), Proceedings of FOIS 2004. International Conference on Formal Ontology and Information Systems, Turin, 4-6. November 2004.

POVEDA-VILLALÓN, M.; GARCIA-CASTRO, R. Extending the SAREF ontology for building devices and topology. Proceedings of the 6th Linked Data in Architecture and Construction Workshop. Londres, United Kingdom. 2018.

RASMUNSSEN, M. H.; HVIID, C. A.; KARLSHOJ, J. Web-based topology queries on a BIM model. Em: Linked Data in Architecture and Construction Workshop, 5. Proceedings […]. Dijon. 2017.

SCHULZL, O.; ORASKARY, J.; BEETZ, J. Lessons Learned from Designing and Using bcfOWL. Proceedings LDAC2023 – 11th Linked Data in Architecture and Construction, jun. 15–16, Matera, Italy. 2023.

SMITH, B. New desiderata for biomedical terminologies. Em: MUNN, K.; SMITH, B. (eds.). Applied Ontology: An Introduction, Frankfurt-Lancaster: Ontos. pp.83-109. 2008.

SMITH, B. Beyond Concepts: Ontology as Reality Representation. Em VARZI, A.; VIEU, L. (eds.), Proceedings of FOIS 2004. International Conference on Formal Ontology and Information Systems, Turin, 4-6. November 2004.

SOUZA, D. L. de; RUSCHEL, R. C. Análise de ontologias para construção civil utilizando ferramentas automáticas baseadas em métricas de qualidade. PARC: Pesquisa em Arquitetura e Construção, Campinas, SP, v. 15, n. 00, p. e024012, 2024. DOI: 10.20396/parc.v15i00.8673829.

USCHOLD, M.; GRUNINGER, M. Ontologies: Principles, methods and applications. Em: The Knowledge Engineering Review. v.11, n.2. 1996.

VINGE, V. The Coming Technological Singularity: How to Survive in the Post-Human Era. Em: Vision-21: Interdisciplinary Science and Engineering in the Era of Cyberspace. LANDIS, G. A. (ed), NASA Publication CP-10129. pp.11-22. 1993.

XIAO G., DING L., COGREL B., & CALVANESE D. Virtual knowledge graphs: An overview of systems and use cases. (“Accessing scientific data through knowledge graphs with Ontop - Cell Press”) Data Intelligence 1(2019), 201-223. doi: 10.1162/dint_a_00011 Received: February 24, 2019; Revised: April 7, 2019; Accepted: April 26, 2019

YOUNG R. I. M.; GUNENDRAN A. G.; CUTTING-DECELLE A. F.; GRUNINGER M. Manufacturing knowledge sharing in PLM: a progression towards the use of heavy weight ontologies. International Journal of Production Research. v.45. n.7. pp.1505–1519. Abril 2007.

ZHAOZHIMING. Advanced RAG Retrieval Strategies Using Knowledge Graphs. In Generative IA. Disponível em: https://medium.com/generative-ai/advanced-rag-retrieval-strategies-using-knowledge-graphs-12c9ce54d2da. Jun, 2024.

ZHENG, C.; WONG, S.; SU, X.; TANG, Y.; NAWAZ, A.; KASSEM, M. Automating construction contract review using knowledge graph-enhanced large language models. Em. Automation in Construction, Vol. 175, 2025. https://doi.org/10.1016/j.autcon.2025.106179.

Published

2026-03-25

How to Cite

MENEGOTTO, José Luis. BIM ONTOLOGY: TOWARD A COGNITIVE ARCHITECTURAL POLICY. LUMEN ET VIRTUS, [S. l.], v. 17, n. 58, p. e12659 , 2026. DOI: 10.56238/levv17n58-069. Disponível em: https://periodicos.newsciencepubl.com/LEV/article/view/12659. Acesso em: 29 mar. 2026.