Local Data Journalism
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Empowering journalists with high-quality data and UChicago rigor.
Investigative journalism increasingly involves digging into large data sets with granular detail on topics such as housing and real estate, policing and crime, voting and elections, education, climate, and government finance.
Analyzing and presenting this information in an engaging, and impactful way takes significant time, computational power, and expertise — at a moment when many newsrooms are strapped for resources and staff.
How it works
Run by the Data Science Institute and the Mansueto Institute, the Local Data Journalism Initiative establishes partnerships between news organizations and university data science teams using the highest caliber data science and artificial intelligence tools and methodologies.
Distinctive approach
What sets this effort apart from existing university data journalism programs is that, rather than attempting to train reporters to be data scientists in a few weeks, we connect them with university faculty and students who will conduct data science projects and provide analyses and visualizations needed to complete their stories.
This empowers journalists to do what they do best: investigate leads; build relationships with sources; and tell powerful, impactful stories — knowing that the data and results they’re reporting have been rigorously analyzed and validated.
Program-at-a-glance
- Program takes place during the summer
- Each team member will have skills relevant to their assigned project
- Local journalists / news outlets are paired with UChicago data science team
- By the end of the summer, journalists receive completed data analyses and engaging visualizations
- Data science team includes on-campus faculty and UChicago students
- Results are validated by the University
How to Apply
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For journalists
If you are a journalist and have an investigative story in mind related to critical issues affecting cities, applications are accepted on an annual basis.
APPLICATION DEADLINE:
Applications are currently closed and will re-open in late 2025 or early 2026.
For students
This opportunity is open to graduate students and advanced undergraduate students in data science.
APPLICATION DEADLINE:
Applications are currently closed and will re-open in late 2025 or early 2026.
Current Projects
The Local Data Journalism Initiative worked during the Summer 2024 with the following journalists and media organizations on critical issues impacting cities, including real estate, transportation, and public finance:
- Maya Dukmasova, Injustice Watch
- Sarah Freishtat, Chicago Tribune
- Matt Kiefer WBEZ Chicago
- Alden Loury, WBEZ Chicago
- Dan Petrella, Chicago Tribune
- A.D. Quig, Chicago Tribune
Faculty Leads
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Christopher R. Berry
William J. and Alicia Townsend Friedman Professor, Harris School of Public Policy and the College; Director, Mansueto Institute for Urban Innovation
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Faculty Advisers
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Philip Garboden
Associate Professor at the Crown Family School of Social Work, Policy, and Practice
Justin Marlowe
Research Professor, Harris School of Public Policy
Student Fellows
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Fatima Irfan
MS candidate in Computational Analysis and Public Policy, Harris School of Public Policy
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Joaquin Pinto
MS candidate in Computational Analysis and Public Policy, Harris School of Public Policy
Austin Steinhart
MS candidate in Computational Analysis and Public Policy, Harris School of Public Policy
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Kevin Bryson
PhD candidate, Department of Computer Science, SUPER (Security, Usability, & Privacy Education & Research) group
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Regina Isabel Medina Rosales
MS candidate in Computational Analysis and Public Policy, Harris School of Public Policy
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Caitlin P.
MS candidate in Computational Analysis and Public Policy, Harris School of Public Policy
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Ana (Anita) Restrepo Lachman
PhD candidate in Psychology, Social Psychophysiology and Neuroendocrinology Lab