Montreal's 311 records shed light on residents' concerns — to a point

Montreal's 311 records shed light on residents' concerns — to a point

Organisation: Montreal Gazette (Canada)

Publication Date: 03/22/2016

Applicant(s)

Size of team/newsroom:large

Description

Five years of service requests from residents to the City of Montreal were analyzed. Records were aggregated by type of request (e.g. broken street lamps, fallen trees, potholes) and by city borough. The results show what residents complain the most about, as well as seasonal and regional differences. But the most important insight from this project was how messy and inconsistent the data was. It took many months of cleaning and munging, with the help of two data scientists, to make any sense of the data. If it was that hard for us, imagine for city bureaucrats who need to make decisions from long-term data. With this project, we started a conversation on better 311 systems and the importance of data validation.

What makes this project innovative? What was its impact?

This was the first time this kind of analysis was made with this municipal data. It showed the city collects the records of service requests but it can't possibly get useful insights out of it, since it's so messy. It was also innovative because it enlisted the help of professional data scientists who are also civic hackers, bringing intense external expertise to the newsroom.

Technologies used for this project:

Tabula to extract data from thousands of pages of PDFs. OpenRefine to standardize categories. PostGIS to geolocate records. SQLite to query the prepared data. DimpleJs to visualize data on the web.
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