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Título
A Meta-modeling Approach to Take into Account Data Domain Characteristics and Relationships in Information Visualizations
Autor(es)
Assunto
Data visualization
Information visualization
Misleading visualizations
Feature identification
Meta-modeling
Clasificación UNESCO
1203.17 Informática
Fecha de publicación
2021
Citación
Vázquez-Ingelmo, A., García-Holgado, A., García-Peñalvo, F. J., & Therón, R. (2021). A Meta-modeling Approach to Take into Account Data Domain Characteristics and Relationships in Information Visualizations. In Á. Rocha, H. Adeli, G. Dzemyda, F. Moreira, & A. M. Ramalho Correia (Eds.), Trends and Innovations in Information Systems and Technologies, WorldCIST 2021 (Vol. 2, pp. 570-580). Springer Nature. https://doi.org/10.1007/978-3-030-72651-5_54
Resumen
[EN]Visual explanations are powerful means to convey information to large
audiences. However, the design of information visualizations is a complex task, because a lot of factors are involved (the audience profile, the data domain, etc.).
The complexity of this task can lead to poor designs that could make users reach
wrong conclusions from the visualized data. This work illustrates the process of
identifying features that could make an information visualization confusing or
even misleading with the goal of arranging them into a meta-model. The metamodel
provides a powerful resource to automatically generate information visualizations
and dashboards that take into account not only the input data, but also
the audience’s characteristics, the available data domain knowledge and even the
data context.
URI
ISBN
978-3-030-72651-5
DOI
10.1007/978-3-030-72651-5_54
Versión del editor
Aparece en las colecciones
- GRIAL. Monografías [13]