#156 Predicting Food Inspection Outcomes Using Open Data

Tom Schenk, Gene Leynes, Gerrin Butler, Raed Mansour from Jon Levy the City of Chicago will present on a predictive model they developed to estimate the riskiest food establishments to assist in the City’s food inspection operations.

Chicago has 15,000 food establishments and conducts nearly 22,000 inspections each year with 38 inspectors. Finding the most serious violations can help reduce exposure to potentially dangerous condition for patrons.

To assist with this, the City of Chicago developed a predictive model to estimate the riskiest locations using data from the open data portal. The model was released as an open source project that can be adopted by other cities, critiqued by other researchers, and improved upon - in the public arena - by the City or others.