Yan, Jiayi; (2025) Developing a 'stakeholder-data requirement' driven data ecosystem of city-level digital twins for urban management use cases. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

The effective development and application of city-level digital twins (CDTs) for urban management rely heavily on efficient data management of heterogeneous data sources within an interoperable and long-lasting common data environment (CDE). However, existing studies have inadequately addressed stakeholder engagement—particularly stakeholder identification and stakeholder requirement (SR) specification—and its influence on data requirements (DRs) in developing city-level CDEs for CDTs. Additionally, the organisational and technical processes required to manage data involving SRs and DRs within a functional, interoperable, and dynamic city-level CDE remain unclear. These challenges are exacerbated in the urban context compared to building or infrastructure settings due to increased complexity in physical assets, stakeholder networks, and their synergies. This research proposes a novel 'stakeholder-data requirement' driven data ecosystem (SDDE) to address these gaps, adopting a design science research (DSR) paradigm. A systematic review of 144 articles was conducted to explore the data environment perspective, followed by semi-structured expert interviews yielding 50.5 hours of data and insights from 22 real-world CDT cases globally. Social network analysis (SNA) was applied to analyse stakeholder roles and SRs, facilitating the development of a general DR framework encompassing data ethics, data security, data availability, and data quality. A six-step roadmap was established to specify use-case-targeted DRs for data sources collection. Building on these findings, the SDDE process model was developed, incorporating functional components (FCs), business processes (BPs), and technical processes (TPs), with a metadata library at its core to streamline the organisational and technical management of dynamic data ecosystems. The SDDE was validated through a case study of the Mashan CDT project, demonstrating significant improvements in urban management efficiency and effectiveness. For example, automated data integration and visualisation tools reduced two months of on-site survey work to a single day, while the semantically centralised metadata library optimised business reporting, facilitated master data management, and enhanced the quality of integrated data models (IDMs). These advancements supported an interoperable and dynamic Mashan CDT, resulting in socio-economic and environmental benefits, including increased citizen satisfaction, financial savings, and land resource protection. Validation using an open data ecosystem framework highlighted improvements in data supply, governance, and user satisfaction. This research significantly enhances the efficiency and efficacy of urban management CDTs by developing an SDDE, innovatively linking stakeholders with data management. It provides valuable empirical insights for practitioners and researchers to advance city-level CDE establishment, bridging the gap between theoretical concepts and practical implementation.

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