Darek Kowalski, creator of parkintoronto.com, pauses at 20 Edward St. in front of the World's Biggest Bookstore, with statistically the third-highest ticket count in the city.
One man’s quest to turn five years of data sets on parking tickets into a searchable database could prove useful for drivers hoping to avoid hefty fines.
Parkintoronto.com was announced Sunday via Reddit, and it’s already racked up more than 4,000 hits in 24 hours, according to its creator.
One quick search and you can find out what hours, days of the week and months most parking tickets have been written for any given street in the city. Almost 50,000 tickets, the most in the city, were given at Sunnybrook hospital, according to the data.
You can even check specific addresses and find out whether your chances of a ticket are more likely at 230 Front St. or 171 Front St. (spoiler: it’s 230).
After finding the data while searching in Open Data Toronto, the site’s creator Darek Kowalski, a self-described “keyboard warrior,” said he “couldn’t not” do something with it.
“I was so shocked by the granularity of the data,” Kowalski said. “I mean, they show the hour when tickets were given out, and I’ve got five years’ worth of this data, how can I not use it?”
Keith McDonald, a spokesperson for Open Data Toronto, said that to their knowledge Kowalski is the first to create a searchable site based on the parking ticket data.
Although developers have created a whole crop of apps for public transit, he said most creations involving parking ticket data are limited.
“We had one person who created a few visualizations,” McDonald said. That person “created a map that shows over time where parking tickets have been issued over the course of one day, like a heat map.”
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In this case, though, it wasn’t searchable or address-specific.
The response to Kowalski’s site has been so positive, he’s already moving forward with plans for an app.
While drivers can currently search the site and make inferences about the likelihood of a ticket in a particular spot, he said the app will take it one step further, more accurately predicting the likelihood of a ticket in any given parking spot.
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