Enhancing Collaboration in Urban Data Governance: A Measurement Framework for Applied Data Visualization
Chien-Yu Lin
Room: 103
2023-10-22T03:00:00ZGMT-0600Change your timezone on the schedule page
2023-10-22T03:00:00Z
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Abstract
The integration of data science, machine learning, and artificial intelligence in urban studies and design promises transformative impacts on cities. While acknowledging that urban complexities transcend data, the concepts of datafication and dataism emphasize the potential to sample, model, and predict urban phenomena through data. This study explores the synergy of collaboration and data visualization in urban data governance. An analytical framework, rooted in the multidimensional collaboration model and guided by theories, elucidates dimensions like Governance, Administration, Autonomy, Mutuality, Norms, and Equality. A combination of qualitative and quantitative research complements the framework, generating indicators to assess the impact of data visualization on data governance. This study contributes to structuring the framework to examine the symbiotic relationship between data visualization, collaboration, and decision-making, propelling transformative urban data governance.