Abstract

The focus of this research-creation project is how data journalism can be learned and applied to the coverage of housing issues in the city of Montreal. In examining this subject, several questions are raised about the nature of data journalism as a subsection of the larger journalistic field. This research aims to investigate how data journalism practices can be learned, taught and incorporated into the existing work of journalism studies, through coverage of the city, housing and gentrification.

In applying a “learning-by-doing” model of research-creation, conducting this project did lead to higher competency in data journalism practices. The results of this experience indicate ways data journalism education could be applied differently in university and mid-career journalism training curricula, namely, using a specialized data journalism project to develop a specific set of data journalism skills and making those skills more accessible by focusing on a localized story. It was also determined that in creating a data journalism project that focused on a specific story—in this case, housing issues in Montreal—there was a need to narrow in on a particular set of skills—namely data analysis, programming and mapping proficiency—similar to how traditional reporters must develop certain skills to cover different beats in a newsroom. This research indicates that a more widespread application of this learning-by-doing model in data journalism training and education has the potential to allow students to more deeply develop specific skill sets that would lend themselves more effectively to the expansive and collaborative practice of data journalism in the industry.