Through the use of automated data capturing, a team of faculty and graduate students at the University of Maryland (UMD), along with a professor from UCLA, created the largest national database of food safety inspection information.

“In the US, such inspections are done by local public health departments, which can take different approaches to conducting, coding and reporting inspection data,” researchers say. “Using this unique, new automated database, foodservice businesses and consumers can monitor and compare food safety practices across the nation.”

The national database was developed by UMD Professor of Computer Science Ben Bederson, UMD Professor of Economics Ginger Jin, UCLA Associate Professor of Business Management Philip Leslie, new PhD graduate Alexander Quinn and UMD PhD graduate student Ben Zou.

According to Bederson, the database uses automated robots to collect data from local government websites. However, Bederson says building the system to reliably collect data from multiple jurisdictions across the US was an enormous challenge.

Another difficulty was developing normalization algorithms to compare data across jurisdictions where the data is very different, researchers say. For some web pages, the team had to write custom “scrapers” to get the data; for others, they had to interpret already available databases.

“Our data robots cover a large number of local jurisdictions across the US, continuously detecting new data posted by each of them and integrating the data into a single, standardized, cumulative database,” says Bederson.

The result is a cost-effective database that is  robust and scalable.

Researchers developed analytical tools that can be used to compare inspection outcomes across localities and states, as well as across chain and individual food outlets, such as restaurants, cafes, convenience stores and grocery markets. These tools can improve inspection efficiency and promote retailer compliance, resulting in a decrease in foodborne illnesses, according to Bederson.

The team has created a regulatory data analytics company Hazel Analytics which, according to Bederson, is a direct outgrowth of its academic collaboration on food safety inspection data funded by the Sloan Foundation.

“As we shared our work with industry players, government agencies such as the FDA and CDC, and other academics, our intuition was confirmed that there was commercial value in our database and analytical approach,” says Bederson.

Hazel Analytics now produces a commercial-grade restaurant inspection database and analytical services for the foodservice industry. The group anticipates the company will start generating revenue this year.

 For non-commercial use, the database is publicly available at at no cost.