Andrea Lezcano Airaldi‡, Jorge Andres Diaz-Pace§, Emanuel Irrazábal‡Corresponding author: Andrea Lezcano Airaldi ( alezcano@exa.unne.edu.ar ) © Andrea Lezcano Airaldi, Jorge Andres Diaz-Pace, Emanuel Irrazábal. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-ND 4.0). This license allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use. Citation:
Lezcano Airaldi A, Diaz-Pace JA, Irrazábal E (2021) Data-driven Storytelling to Support Decision Making in Crisis Settings: A Case Study. JUCS - Journal of Universal Computer Science 27(10): 1046-1068. https://doi.org/10.3897/jucs.66714 |  |
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.