Abstract
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.
| Original language | English |
|---|---|
| Number of pages | 27 |
| Journal | Environment and Planning B: Urban Analytics and City Science |
| DOIs | |
| Publication status | E-pub ahead of print/First online - 25 Mar 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
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SDG 16 Peace, Justice and Strong Institutions
Keywords
- ITC-HYBRID
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