What Makes for Great Data Journalism?

Abstract

This study examines the quality of winners and finalists in major national and international data journalism awards. We completed a content analysis of data projects submitted by Canadian media to three journalism associations—the Online News Association, the Global Editors Network and the Canadian Association of Journalists—as far back as the first award in this category in 2012. Our research addresses how journalists executed what could be considered excellent data journalism. Our findings point to a lack of accepted standards regarding what is considered as excellence. The quality of the projects was limited by two key factors: the use of free online options such as Google Maps that were not easily customizable; and the number of practitioners who worked on the data projects largely within traditional journalism frameworks. The most used visual elements were dynamic maps, graphs and video. With respect to interactivity, all but one of the projects contained an interactive element. The most popular interaction techniques were inspection and filtering, considered entry-level techniques in the field of information visualization. These techniques suggest a need for collaborative interdisciplinary approaches to data journalism, and further study on the implications of tools such as Google Maps on practice.