Urban digital twins (UDTs) were first discussed in 2018. Seven years later, we ask: What has been their contribution to urban planning and decision making so far? Here, we systematically review 88 peer-reviewed articles to map and compare UDTs’ ambitions with their realized contributions. Our results indicate that despite the vast technical developments, socio-technical challenges have remained largely unaddressed, causing many of UDTs’ ambitions to remain unrealized. We identify three categories in these socio-technical challenges: interdisciplinary integration (II), consensual contextualization (CC), and procedural operationalization (PO). Accordingly, we consolidate a socio-technical research and development agenda to realize the ambitions of UDTs for urban planning and decision making: Augmented Urban Planning (AUP).

We propose a mathematical framework for developing social-choice games that are designed to mediate decision-making processes for city planning, urban area redevelopment, and architectural configuration of urban housing complexes. The proposed framework features a digital serious gaming approach for participatory design to support transparency and inclusion in the process of decision-making and ensure an equitable balance of sustainable development goals in spatial design outcomes. The mathematical process consists of a Markovian design machine for balancing the design decisions of actors, a massing configurator equipped with fuzzy logic and multi-criteria decision analysis, algebraic graph-theoretical accessibility evaluators, and automated solar-climatic evaluators using geospatial computational geometry. We demonstrate the effectiveness of the framework by implementing a multi-player online game that facilitates a participatory decision-making workshop for forming multi-functional building complexes by providing a generative configurator equipped with automated appraisal/scoring mechanisms for revealing the aggregate impact of alternatives. The EquiCity game empowers a group of decision-makers to reach a fair consensual spatial design by mathematically simulating many rounds of reasonable trade-offs between their decisions, with different levels of interest or control over various types of investments. The novelty of the framework is in its capability to encompass decision-making about the most idiosyncratic aspects of a site related to its heritage status and cultural significance to the most generic aspects such as balancing access to sunlight for the site while respecting ‘the right to sunlight’ of the neighbours of the site, ensuring coherence of the entire configuration with regards to a network of desired closeness ratings, the satisfaction of a programme of requirements, and intricately balancing individual development goals in conjunction with communal goals and environmental design codes.

Urban Digital Twins (UDTs) were first discussed in 2018. Seven years later we ask: What has been their contribution to urban planning and decision-making so far? Here, we systematically review 84 peer-reviewed articles to map and compare UDTs’ ambitions with their realized contributions. Our results indicate that despite the vast technical developments, socio-technical challenges have remained largely unaddressed which caused much of the UDTs’ ambitions to remain unrealized. We identify three categories in these socio-technical challenges: interdisciplinary integration (II), consensual contextualization (CC), and procedural operationalization (PO). Accordingly, we consolidate a socio-technical research and development agenda to realize the ambitions of UDTs for urban planning and decision-making: Augmented Urban Planning (AUP).

Urban Digital Twins (UDTs) have emerged as integrated collections of urban data and urban models aspiring to enhance urban planning and decision-making processes. However, current UDTs often fail to connect siloed disciplines, represent diverse stakeholder views, or adapt to the dynamic nature of planning processes. Realizing UDTs potentials is hindered by these socio-technical challenges, we developed and validated FMU Ontology to address them. FMU Ontology provides a set of semantic representations that (1) promote interoperability and integration across disciplinary data and models, (2) enable developing and using a network of stakeholder-specific UDTs that facilitate engagement and consensus-building, and (3) embed these within planning processes to allow UDTs to adapt as stakeholders’ questions and priorities evolve. Furthermore, we validate the efficacy of FMU Ontology through consistency and competency tests. Lastly, in a case study on strategic urban densification in Eindhoven, the Netherlands, we demonstrate how FMU Ontology enables the adaptive and collaborative use of UDTs, addressing key challenges in urban planning and decision-making.