Richmond blogs River City Rapids and 100 Word Minimum bring to our attention a New York Times article that highlights the role data mining can play in predicting, and in turn preventing, crime. The case study featured is …. (drumroll): Richmond.

From the article:

RODNEY MONROE, the police chief in Richmond, Va., describes himself as a lifelong cop whose expertise is in fighting street crime, not in software. His own Web browsing, he says, mostly involves checking golf scores.

But shortly after he became chief in 2005, a crime analyst who had retired from the force convinced him to try some clever software. The programs cull through information that the department already collects, like 911 and police reports, but add new streams of data about neighborhood demographics and payday schedules, for example, or about weather, traffic patterns and sports events to try to predict where crimes might occur.

“It sounded nutty at first,” Mr. Monroe recalled, “but the more and more you get into it, the more sense it makes.”

The technology, for example, pointed to a high rate of robberies on paydays in Hispanic neighborhoods, where fewer people use banks and where customers leaving check-cashing stores were easy targets for robbers. Elsewhere, there were clusters of random-gunfire incidents at certain times of night. So extra police were deployed in those areas when crimes were predicted.

The crime rate in Richmond declined about 20 percent last year, and it is down again this year.

I post this information on this site because, while the story does not reference Petersburg, innovations are innovations, and given Petersburg’s focus on prevention in addition to correction, this idea may be of some interest locally.