Towards a well-being-oriented framework for urban digital twins

Urban well-being is gaining prominence as a critical pillar of sustainable development practice and urban planning; however, digital twin technology continues to focus predominantly on physical infrastructure. This paper introduces an exploratory conceptual framework for incorporating urban well-being indicators into urban digital twin platforms, utilizing New Zealand's Living Standards Framework (LSF) and adopting a policy-oriented approach to selecting well-being indicators. Through consultation with experts and a literature review, we identified six policy-relevant proxies: carbon emissions, drinking water quality, road fatalities, crime rates, work commute times, and internet access, which reflect the environmental, social, and economic dimensions of well-being. Historical data from 2017 to 2023 was operationalised in a Python-based analytical dashboard, which generates descriptive statistics, benchmarks, correlations, and Autoregressive Integrated Moving Average (ARIMA) forecasts. The study also assessed the technical feasibility of urban well-being indicators using publicly available open-source digital twin platforms such as Eclipse Ditto and FIWARE. The results indicate that integration is technically feasible; however, they are constrained by schema incompatibilities, limited native analytics capabilities, and questions of scalability regarding how proxies relate to urban well-being. As a proof-of-concept study, it explored how digital twin technology could be reshaped to support holistic, citizen-oriented objectives for well-being and complement participatory and multi-criteria approaches. • Introduces a framework to embed well-being indicators in urban digital twins. • Uses New Zealand's Living Standards Framework for indicator selection. • Develops a Python dashboard with descriptive, correlation, and ARIMA analyses. • Tests feasibility with Eclipse Ditto and FIWARE open-source DT platforms. • Proposes a hybrid architecture linking socio-economic data with DT systems.