At the core of the smart city movement is the use of community data to make better decisions about policy and the development of the urban environment. This data can be widely collected by official government agencies through sensors, surveyed from social media or other crowd sources, or it can be drawn from small interactions with community groups and volunteer civic leadership. It's easy to picture the TV police "command center" where crimes are solved in real-time on large displays. But beyond the data on where crime has occurred, how can we evaluate the effectiveness of policing in a community, or identify the cause of large differences between the official records of crime and undocumented cases? How can we utilize social media data to understand the changes in public sentiment as a result of major events? While there are many ways to analyze such data, urban areas represent a cross-section of diverse stakeholders, citizens, and community interests whose qualitative data and insight are not always incorporated within geospatial analysis. Consequently, we need methods of analysis that cultivate participation from these diverse groups while facilitating rigorous exploration and reasoning about community data. We are currently developing these methods of analysis through the use of sketch-based interaction, geovisualization, and participatory design.
To explore an example of our, try out this inetractive demo of health data about Atlanta created by Xiaoxue (Ellie) Zhang.