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dc.contributor.author
Lezcano Airaldi, Andrea Fernanda
dc.contributor.author
Diaz Pace, Jorge Andres
dc.contributor.author
Irrazábal, Emanuel Agustín
dc.date.available
2023-08-14T15:37:44Z
dc.date.issued
2021-10
dc.identifier.citation
Lezcano Airaldi, Andrea Fernanda; Diaz Pace, Jorge Andres; Irrazábal, Emanuel Agustín; Data-driven storytelling to support decision making in crisis settings: A case study; Graz University of Technology; Journal of Universal Computer Science; 27; 10; 10-2021; 1046-1068
dc.identifier.issn
0948-695X
dc.identifier.uri
http://hdl.handle.net/11336/208180
dc.description.abstract
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.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Graz University of Technology
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
BEST PRACTICES
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COVID-19
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DATA STORYTELLING
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EMPIRICAL STUDY
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INFORMATION VISUALIZATION
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Otras Ciencias de la Computación e Información
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Ciencias de la Computación e Información
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CIENCIAS NATURALES Y EXACTAS
dc.title
Data-driven storytelling to support decision making in crisis settings: A case study
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-08-11T10:44:10Z
dc.journal.volume
27
dc.journal.number
10
dc.journal.pagination
1046-1068
dc.journal.pais
Austria
dc.journal.ciudad
Graz
dc.description.fil
Fil: Lezcano Airaldi, Andrea Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentina. Universidad Nacional del Nordeste; Argentina
dc.description.fil
Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
dc.description.fil
Fil: Irrazábal, Emanuel Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentina. Universidad Nacional del Nordeste; Argentina
dc.journal.title
Journal of Universal Computer Science
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://lib.jucs.org/article/66714/
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