The talk will focus on the question of how we can build resources from high frequency data to address long-standing challenges in urban policy. I will refer to the notion of digital twins and draw upon experience from two urban data science projects to highlight some epistemological questions that arise in interpreting urban dynamics captured in high frequency data. I will conclude with a set of propositions on the promise data science holds for solving long-term challenges in urban policy.

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