Sovereign City DNA: An Integrated Metropolitan Systems Framework

Large-scale metropolitan programmes are commonly organized through sectoral institutions, projects, contracts and infrastructure systems, while the performance of the city as a whole depends on relationships among governance, economics, finance, infrastructure, institutions, people, environment, mobility, data, culture, resilience and learning. This paper develops Sovereign City DNA as an integrative metropolitan systems framework for representing those relationships. The framework is not presented as a biological model, a literal genome, or an established academic standard. Nor does it claim originality for the broader city-DNA or urban-genome metaphor. Its contribution is a practitioner-originated synthesis that organizes twelve interdependent capability domains into a metropolitan relationship architecture intended to support diagnosis, operating-model design, adaptation and responsible replication. The paper situates the framework against established work on metropolitan governance, functional urban systems, urban resilience, digital urban governance, complex adaptive systems and integrated monitoring. It distinguishes copying a physical city design from replicating metropolitan capability. A conceptual interaction model is proposed in which governance and institutions establish decision rights; economic and financial systems allocate resources; infrastructure, mobility and environmental systems deliver services; human and cultural systems create capability and legitimacy; digital systems provide sensing and coordination; resilience protects continuity; and learning/adaptation modifies the system over time. The paper identifies falsifiable propositions, including whether stronger cross-domain coherence is associated with better operating continuity, adaptation and service integration. Current maturity is conceptual and evidence-informed rather than operationally validated. The framework therefore requires structured expert review, case comparison, construct validation and pilot application before it can support claims of predictive or causal performance