CFP: Digital Twins for Cities
Title:  CFP: Digital Twins for Cities
Source:  Others
Category:  Other Special Topics
Employer:  Environment and Planning B: Urban Analytics and City Science
Deadline:  11/30/2022 12:00:00 AM
Post Date:  6/20/2022 12:00:00 AM
Contact:  Claudia Yamu:
Describe:  Digital transformation in urban planning is gaining momentum, and with it, digital twins for cities are on the rise. However, a coherent position on what city/urban digital twins are, has not yet emerged. Different perspectives emphasize various aspects of what city/urban digital twins can be in different circumstances. Examples range from emphasizing emerging technologies and advanced data analytics to revisiting existing digital techniques and technologies with a fresh outlook; and include interdisciplinary perspectives that conceptualize city/urban digital twins as an innovative tool for decision-making, and/or a novel user-friendly participatory mechanism, and form of communication, with stakeholders and citizens. The concept of a digital twin is not new. The term was first used by David Gelernter, and first applied by Michael Grievesin manufacturing two decades ago. According to Grieves, a digital twin concept consists of three main elements: (1) a physical product in real space; (2) virtual products in virtual space; and (3) the connections of data and information that ties the virtual and the real product together. Even this seemingly simple and unproblematic characterization of digital twins throws up unresolved issues when it comes to digital twins for cities. At present, the term digital twin is used for a variety of digital simulation models that run alongside real-life social, economic, and physical processes and systems. However, digital twins for cities are still in their infancy as digital twin experiments often involve visual urban representations and neglect real-time analytics, as well as the complexities involved in real-world urban governance and policy. While often matured and also experimental technologies are applied, there remains a lack of in-depth critical reflection on integration maturity, alongside issues relevant to policy, governance and practice, such as participation, transparency, accountability, and interoperability. Further challenges for city/urban digital twins are connected to how close the digital twin is to the ‘real’ system, however this ‘real’ system might be interpreted by modelers. This is also reminiscent of discussions about abstractions of the model, input versus output, and gained results, representing a longstanding conundrum. Let us remember that urban digital twins are cost and time-intensive virtual models. City/urban digital twins are per se not self-evident, and no one digital twin fits all purposes. However, the transferability of digital twin results to urban policy recommendations is key in enabling equity and sustainability in future cities. This is an important consideration for stewardship that determines the context of the digital twin and how it is used in the planning process. Consequently, stewardship, data policy and management, and application context are influential for the digital twin content. Given the variety of conceptualizations for digital twins, it is not yet clear how such broad concepts can be translated into a meaningful tool for decision-making in cities, taking into consideration the following: (a) the practical implementation and operationalization of digital twins in urban planning; (b) how close are digital twins to ‘reality’; (c) how are sensors used and which physical features are sensed to digitally reconstruct this reality; (d) what are the distinctive tangible and non-tangible features or city/urban digital twins that are needed at different city scales; (e) in what ways does a digital twin connect to governance, for example through participatory planning; and (f) how can these connections be configured to be meaningful for planning processes? We are seeking research articles that employ pertinent and relevant state-of-the-art methods for digital twins with data stewardship, novel and innovative models related to processes and their outcomes, comparative simulation techniques, and comparative case stu