Sean Thornton

Data-Smart City Solutions
Sean Thornton is a Program Advisor for the Civic Analytics Network at Harvard's Ash Center for Democratic Governance and Innovation, and writer for Ash Center publication Data-Smart City Solutions.  Based in Chicago, Sean holds joint Masters’ degrees from the University of Chicago in Public Policy and Social Service Administration. His work has spanned the city's public, philanthropic, and nonprofit sectors.
The project to collect real-time data on Chicago's environment and urban activity launched in 2016 and continues to evolve.
Monitoring virus-laden mosquitoes is nothing new, but forecasting their next move through predictive modeling is.
How analytic data has shaped the tone of Chicago's beaches.
Goose Island is transitioning from an industrial hub to a tech-focused one.
Measurements and metrics are essential to becoming a smart city, and IoT sensors provide the key to do this in real-time.
Using an analytics-based method, Chicago discovered critical violations earlier than if it had used the traditional inspection procedure.
Chicago’s latest major data set release is a list and map of “problem landlords,” or residential building owners across the city that have racked up numerous citations for failing to provide tenants with basic services and protections.
With continued—and even formalized—relationships between individuals, organizations and sectors, the city's data-driven innovations could transform how governments handle public health issues, both internally and externally.
The Chicago School of Data is less of an academic discipline and more of a method for cooperative, data-driven progress united by one key principle—that data, as public good, is one that is at the service of all people.
At Chicago's Safer Communities hackathon, developers were tasked with making public safety apps more accessible via mobile devices.
Cities around the country are pushing their data into the public space. But shaping that data to solve real-world problems is what really counts.
The term 'big data' may imply that data collection and analysis is a simple process, but time and cost have told local governments otherwise.