Moroni Computational Urban Science (2025) 5:17 https://doi.org/10.1007/s43762-025-00174-0 ORIGINAL PAPER Open Access © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Computational Urban Science Insurmountable limitations of city-scale digital twins? On urban knowledge and planning Stefano Moroni 1* Abstract Digital twins are enjoying widespread and growing success in both theoretical and practical applications. A recent development that is gaining increasing traction is the application of digital twins to cities. The aim of this article is to discuss whether there are inherent limitations in this case. At present, the scientific literature on urban digital twins is dominated by “technical” approaches. Critical investigation of digital twins – especially from a philosophi- cal perspective – is still at its beginnings. This article aims to contribute to this line of inquiry. It is mainly theoreti- cal and analytical. On the basis of a specific conceptual framework, it examines digital twins and their applica- tions in urban contexts. It starts by distinguishing among simple, complicated and complex systems, and reaches the conclusion that, while using digital twins is generally appropriate (and often helpful) in the first two of these systems, there are some structural limitations on their use in the case of complex systems. In the latter case, inher- ent limitations depend on certain distinctive aspects of complex systems, such as their emergent and unpredictable nature, and the role played in this regard by “dispersed knowledge” (that is, is a form of diffused practical knowl- edge that is crucial for the functioning of large urban systems but that cannot be collected and re-unified because, as a coherent and integrated whole, it does not and cannot exist anywhere). Keywords Digital twins, Computation, Urban, City, Planning 1 Introduction Recently, digital twins have become of widespread inter- est in both theory and practice. 1 A digital twin is a digital representation of a system, process or artifact; that is, it is a digital replica, a virtual duplicate, of a physical real- ity. What digital twins have in common with traditional simulations is that in both cases the focus is on models believed (or, at least, hoped) to have a dynamic behav- iour which is sufficiently similar to another (real) system for the former to be used and studied in order to learn about the latter (Winsberg, 2009, p. 836). What is usu- ally considered typical of digital twins is that the model is strictly and continuously associated – coupled – with the simulated system (Tomko & Winter, 2019; Wright & Davidson, 2020). Sensor networks and smart devices provide a continuous flow of information from the real system to the digital twin: in fact, one of the features usually mentioned to distinguish digital twins from tra- ditional simulations is the fact that the former represent their physical counterpart “in real-time” thanks to an active and continuous data flow from the physical coun- terpart to the digital twin itself (Gitahi & Kolbe, 2024; *Correspondence: Stefano Moroni stefano.moroni@polimi.it 1 Department of Architecture and Urban Studies, Polytechnic University of Milan, Via Bonardi 3, Milano 20133, Italy 1 A search for “digital twins” in Scopus (and considering title, abstract, and keywords) found more than 29,000 entries (in February 2025).