Data journalism and ethics: best practices in the winning projects (DJA, OJA and Sigma awards)

Abstract

Data journalism is a consolidated specialization in the newsrooms of many of the world's media outlets. Despite this, little research has been conducted on the ethical principles followed in this field of journalism. Data journalism uses different types of software to find its stories by statistically analyzing large datasets. Our research examines the winning projects of the Data Journalism Awards, Sigma Awards, and Online Journalism Awards, the last in the data journalism category, between 2012 and 2020. Using qualitative content analysis, we analyzed these projects from a three-fold ethical perspective: verification and data analysis, transparency, and privacy. Our main findings show that the winning projects complied with verification and data analysis, which is a standard practice to cross-check data from various sources and contextualize them adequately. In contrast, transparency and privacy principles were followed to a lesser extent. In light of these results, we propose that future research should focus on the perceptions of data journalists and users regarding the ethical standards that these projects meet.