Data-driven storytelling helps to communicate facts, easing comprehension and decision making, particularly in crisis settings such as the current COVID-19 pandemic. Several studies have reported on general practices and guidelines to follow in order to create effective narrative visualizations. However, research regarding the benefits of implementing those practices and guidelines in software development is limited. In this article, we present a case study that explores the benefits of including data visualization best practices in the development of a software system for the current health crisis. We performed a quantitative and qualitative analysis of sixteen graphs required by the system to monitor patients' isolation and circulation permits in quarantine due to the COVID-19 pandemic. The results showed that the use of storytelling techniques in data visualization contributed to an improved decision-making process in terms of increasing information comprehension and memorability by the system stakeholders.

In the field of Information Visualization, storytelling techniques help to communicate facts and enhance comprehension. The use of data storytelling best practices can inform the process of creating narrative visualizations and increase the quality of charts used in software applications by improving aspects such as memorability or engagement, for instance, supporting end users in the decision-making process. The main goal of this doctoral research is to develop a method for assessing and improving the quality of narrative visualizations in software products, like scatter plots, line, bar, or pie charts, among others. This has included a case study and a systematic mapping study.

In recent years, there has been a growing interest in integrating data visualizations into narrative stories to effectively convey information and knowledge. By leveraging the best practices established in the literature, narrative visualizations can reduce the cognitive workload associated with chart comprehension. However, since it is critical and challenging to assess the results, several methodologies have been proposed in this regard. In this article, we present a systematic mapping study of ninety-five data storytelling and information visualization studies. Our goal is to collect and summarize current definitions of “data storytelling” reported in the literature, the best practices for designing narrative visualizations, and evaluation criteria and methods to assess them. As main contributions, we derive a working definition of data storytelling, distinguishing among the concepts involved, and provide an overview of design guidelines to assist practitioners and researchers in creating narrative visualizations. In addition, we characterize the main evaluation criteria and methods. Our findings highlight the need for more out-of-the-box, ready-to-use evaluation tools that allow a rapid and iterative assessment of narrative visualizations.