Cities are in dire need for quantitative metrics to assess performance of urban neighborhoods across cities and support decision making processes for resource allocation. Currently, important decision about zoning regulations, the spatial distribution of resources and subsidies for businesses are decided on a daily basis with little to no data-driven metrics (Bettencourt and West, 2010; Glaeser et al., 2015). Till recently, data availability was a main barrier in measuring urban performance across cities and countries in a consistent framework, which was broken in past years with the availability of new and open data sources.
This course will familiarize students with research on urban informatics, a young developing field in computational social science. The emphasis of the course is conceptual - that is, how can data be used to measure and investigate spatial, social and economic urban phenomena with the goal of informing decision makers in policy and planning?
Through a series of discussions on recent literature and basic introduction to data analysis (using R), students will develop critical thinking about answering research questions with data while exploring the potential and perils of working with data. Main subjects include data collection and biases, data-driven metrics, data visualisation and mapping.
- מורה: טליה קאופמן