Data-driven Storytelling to Support Decision Making in Crisis Settings: A Case Study
| Autor: | Emanuel Irrazábal, Jorge Andres Diaz-Pace, Andrea Lezcano Airaldi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Knowledge management
General Computer Science business.industry Computer science Best practice Software development COVID-19 QA75.5-76.95 data storytelling Theoretical Computer Science empirical study Information visualization Data visualization Empirical research infor Electronic computers. Computer science best practices Narrative Software system information visualization business Storytelling |
| Zdroj: | Journal of Universal Computer Science, Vol 27, Iss 10, Pp 1046-1068 (2021) JUCS-Journal of Universal Computer Science 27(10): 1046-1068 |
| ISSN: | 0948-6968 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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