Quality standards in data journalism: Sources, narratives and visualizations in the data journalism awards 2019

Abstract

The purpose of this study is to examine the characteristics of the most internationally recognized data journalism projects, with the aim of providing an in-depth snapshot of the current situation as well as identifying the common elements in the exercise of this journalistic practice. A content analysis is carried out to dissect 42 projects nominated for the Data Journalism Awards 2019, which were selected by the Global Editors Network for complying with the quality standards of this specialty. The pieces are examined from three different perspectives: the features of the story, the data, and the visualizations used. Among other findings, the results show the transversality of this treatment technique, which can be shaped to be applied in any subject area, and the prevalence of topics such as health, science, and the environment, partly due to circumstances related to the climate emergency together with the current environmental challenges. There is a wide variety of sources, but a strong dependence on documentaries from governments or public offices (59.52%) can be observed as well as widespread use of infographics as a form of visualization (45.24%), generally presented as scrollytelling. It is also deduced that quality is conditioned by the nature of the sources, the innovative character of the analysis carried out, the way in which the information is compiled, and the complexity of the visualizations involved. Data journalism is an ever-changing journalistic practice, hence the necessity to rethink its quality parameters as it evolves as a specialization to adapt them to the new forms of materializing information.