Published 2026-01-07
Keywords
- Artificial Intelligence,
- Applied Ontology,
- Data,
- City,
- Complexity
How to Cite
Copyright (c) 2026 Stefano Borgo, Camilla Perrone
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Abstract
In recent years, cities have undergone a dramatic evolution as they become increasingly connected, data‐rich environments. Urban artificial intelligence (AI) has emerged as a transformative force, empowering city planners, policymakers, and researchers to address complex challenges ranging from resource management to public safety. However, the sheer abundance of data in contemporary urban settings also presents significant ontological challenges that become even more crucial when undertaking urban planning. These challenges revolve around the conceptualisation, classification, and integration of heterogeneous data sources into coherent models capable of supporting intelligent decision-making. In this article, we examine these ontological issues, discuss existing frameworks that aim to unify fragmented information, and explore the practical implications for urban AI applications. The thesis is that ontologies, which are structured and formal representations of knowledge, offer a powerful tool to address the challenges outlined above, while serving as a blueprint for defining, categorising, and interrelating the entities present in urban environments and put to work in urban planning.
Downloads
References
- Batty, M. (2007). Cities and complexity: understanding cities with cellular automata, agent-based models, and fractals. The MIT Press.
- Batty, M. (2013). The new science of cities. MIT Press.
- Bettencourt, L. M. (2014). The uses of big data in cities. Big data, 2(1), 12-22.
- Borgo, S., Borri, D., Camarda, D., & Stufano Melone, M. R. (2021). An ontological analysis of cities, smart cities and their components. In Technology and the City: Towards a Philosophy of Urban Technologies (pp. 365-387). Cham: Springer International Publishing.
- Borgo, S., Ferrario, R., Gangemi, A., Guarino, N., Masolo, C., Porello, D., Sanfilippo, E. M., & Vieu, L. (2022). DOLCE: A descriptive ontology for linguistic and cognitive engineering. Applied Ontology, 17(1):45–69.
- Calegari, R., Ciatto, G., & A. Omicini (2020). On the integration of symbolic and sub-symbolic techniques for xai: A survey. Intelligenza Artificiale, 14(1):7–32.
- Cugurullo, F. (2021). “Frankenstein Urbanism: Artificial intelligence and the city”, in Marvin, S., Luque-Ayala, A., and McFarlane, C. (eds), Smart Urbanism: Utopian Vision or False Dawn?, Routledge, London, pp. 200–215
- Cugurullo, F., Caprotti, F., Cook, M., Karvonen, A., MᶜGuirk, P., & Marvin, S. (2024). The rise of AI urbanism in post-smart cities: A critical commentary on urban artificial intelligence. Urban studies, 61(6), 1168-1182.
- Mattern, S. (2021). A City is Not a Computer: Other Urban Intelligences. Princeton, NJ: Princeton University Press.
- Portugali, J. (Ed.). (2021). Handbook on cities and complexity. Edward Elgar Publishing.
- Romele, A. The datafication of the worldview. AI & SOCIETY, 38:2197–2206, 2023.
- Saramago, J. (2018). Último Caderno de Lanzarote. O diário do ano do Nobel. Ed. Porto Editora, pp. 272. ISBN: 978-972-0-03128-0
- Stufano Melone, M. R., Borgo, S., & Camarda, D. (2024, July). City Interactions in Urban Planning: The Square Example from an Ontological Analysis Point of View. In International Conference on Computational Science and Its Applications (pp. 448-455). Cham: Springer Nature Switzerland.
- Romele, A. (2023). Digital habitus: a critique of the imaginaries of artificial intelligence. Routledge.
- Zins, C. (2007). Conceptual approaches for defining data, information, and knowledge. Journal of the American society for information science and technology, 58(4), 479-493.