Evaluating the transparency in reference data journalism Study of the stories published between 2018 and 2019

Abstract

The approval of laws that provided access to information and promote the transparency of institutions favored the establishment of data journalism as a journalistic practice. This specialization arises in favor of transparency, so incorporating indicators that reduce opacity of the media industry is necessary to add credibility and quality to the published story. This research aims to examine the level of transparency in the best data journalism stories published worldwide between 2018 and 2019. It also aims to check whether the typology of sources and data affects opacity and to classify the pieces according to the degree of transparency. Through a descriptive and inferential analysis of the candidate projects for the Data Journalism Awards 2019 and the Sigma Awards 2020 (n=80), a wide range of improvement in terms of transparency is detected. While the vast majority of pieces mention the source directly (91.4%), access to the methodology (48.8%) and to the data (20%) is quite limited. The multiple correspondence analysis reveals three groups of stories, many of which belong to the highest level of opacity. Among other findings, it is concluded that the type of sources and data incorporated does not influence on the level of transparency.