Computational journalist Cheryl Phillips leads Big Local News, which collects, processes and shares governmental data that are hard to obtain and difficult to analyze; partners with local and national newsrooms on investigative projects across a range of topics; and makes it easy to teach best practices for finding stories within the data. Among other projects, the team of Stanford faculty, data journalists, students and researchers is doing work to inform the public about disparities in criminal justice, environmental and economic impacts of forest fires, local government accountability through audits, the integrity of elections at the state level, and root causes of out-of-reach home prices in local markets.
Big Local NewsBig Local News is launching a platform that will allow journalists to collaborate on data projects, archive their data with the Stanford Digital Repository and share it with the public. Eventually, the platform will support tools to help journalists manage requests, clean messy data, standardize information, perform analyses and visualize their data.
Phillips and her team have held events for reporters and editors to foster newsroom collaborations and trained dozens of journalists in the use of data that Big Local News collected and archived. In addition, a Big Local News course for graduate and undergraduate students at Stanford was taught for the first time in fall 2018 and again in fall 2019. Big Local News began as the Stanford Open Policing Project, which brought to light patterns of bias in police stops of motorists. The project initially collected 250 million records from 33 states, and recently it gathered and analyzed new data showing evidence of racial discrimination at not just the state patrol level but also in local police departments. Multiple newsrooms are now requesting traffic stop data from their local governments to add to the Big Local News repository.
Learn more at: Big Local News