Stanford Open Policing Project — San Francisco data
This is the project’s main dataset, providing standardized traffic-stop records that make it possible to compare where stops happen, when they happen, and what outcomes follow.
Kepler.gl
Kepler.gl was referenced as a visual and conceptual benchmark for map design, particularly in exploring how dense geospatial data can be effectively represented and communicated.
A large-scale analysis of racial disparities in police stops across the United States
Pierson et al. analyze nearly 100 million traffic stops and show how large-scale stop data can reveal racial disparities in stop decisions and search outcomes.
Racial Disparities in Traffic Stops
This PPIC report examines 3.4 million California traffic stops and compares disparities across time of day, agency type, and traffic violation type.
Stanford Open Policing Project — Findings
The project’s findings page summarizes the broader statistical patterns behind the dataset and gives context for how racial disparities appear across agencies and stop types.
Officer bias, over-patrolling and ethnic disparities in stop and search
This study helps frame stop-and-search disparities as the result of both officer behavior and department-level patterns, which is useful when interpreting concentrated stop activity in a single city.