The Stanford Open Policing Project

On a typical day in the United States, police officers make more than 50,000 traffic stops. Our team is gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country. Our goal is to help researchers, journalists, and policymakers investigate and improve interactions between police and the public.

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The Open Policing Project

Currently, a comprehensive, national repository detailing interactions between police and the public doesn’t exist. That’s why the Stanford Open Policing Project is collecting and standardizing data on vehicle and pedestrian stops from law enforcement departments across the country — and we’re making that information freely available. We’ve already gathered over 200 million records from dozens of state and local police departments across the country.

We, the Stanford Open Policing Project, are an interdisciplinary team of researchers and journalists at Stanford University. We are committed to combining the academic rigor of statistical analysis with the explanatory power of data journalism.

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See the data behind our findings, and learn how to use it in your own analysis.

Who we are

Phoebe Leila Barghouty

Data Journalist, Stanford Computational Policy Lab

Bethney Bonilla

Data Journalist, Big Local News

Sam Corbett-Davies

Ph.D. Candidate, Computer Science

Sharad Goel

Assistant Professor, Management Science & Engineering

Daniel Jenson

Engineer, Stanford Computational Policy Lab

Walter Kim

Engineer, Stanford Computational Policy Lab

Joe Nudell

Engineer, Stanford Computational Policy Lab

Jan Overgoor

Ph.D. Candidate, Management Science & Engineering

Cheryl Phillips

Lorry I. Lokey Visiting Professor in Professional Journalism, Communication

Emma Pierson

Ph.D. Candidate, Computer Science

Vignesh Ramachandran

Stanford Computational Journalism Lab

Eric Sagara

Senior Data Journalist, Big Local News

Amy Shoemaker

Data Scientist, Stanford Computational Policy Lab

Ravi Shroff

Assistant Professor, Applied Statistics, Social Science, and Humanities at New York University

Camelia Simoiu

Ph.D. Candidate, Management Science & Engineering