Defense of Manuela Garretón

Abstract

In a data-driven society, data acquires a fundamental role for public policy, since we trust them to make decisions that affect our lives. Most people obtain data through visualizations published in different media. It is through these encounters that citizens become familiar with the world of politics and form opinions on subjects that affect society, defining a part of public debate. This debate is essential for the process of creating a public policy. Several stages are recognized in this process. The first and most critical of these stages is agenda setting, when a problem is defined and alternative solutions are discussed, attracting or losing public attention and where the media have a significant influence.

Data visualizations published in news media have become increasingly important, as they help citizens to understand complex issues, and therefore influence the way readers form an opinion about it. They are typically part of data stories, a genre of long-form data journalism that combines text, infographics, statistical charts, and various other types of visual artifacts—such as photographs, videos, and illustrations.

In this investigation, we will understand data visualization as part of data stories and as a continuous process from an encoding phase (translation of data into visual elements) by the authors to a decoding phase (interpretation of representations in order to understand the data) by the audience. Data stories published in the media usually define a problem facing society and become part of the agenda setting stage of public policy. It is important therefore that they should be designed effectively so that they form part of public debate in a data-driven society. The literature contains various frameworks which guide the design process of data visualization, however, we found only one that guides the process of transforming data into visual stories (Lee et al., 2015). In this study we enquire whether existing frameworks are able to integrate the factors involved in the encoding and decoding phases so as to ensure that the information presented leads users to the interpretation that the authors intended.

The object of this research is therefore to understand data stories in the agenda setting stage, in order to identify key aspects to be considered for the future implementation of an integrated framework to guide the process of data story design.

This research is broken down into three stages, which separately investigate aspects that are critical for proposing a design framework. The main methodology used is the Design Studies Research (Kuechler & Vaishnavi, 2012). The first stage is a survey of data stories literature with a special focus on the factors that determine the process of transforming data into visual stories. In the second stage we seek to unveil the communicative role of data visualization within data stories (Garretón et al., 2023a). The third, is an empirical research about the effects of data stories on changing attitude towards a presented topic (Garretón et al., 2023b). Our findings contribute to a growing body of literature on how visual artifacts may be used to inform and influence public opinion and debate.