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Título
MetaViz – A graphical meta-model instantiator for generating information dashboards and visualizations
Autor(es)
Palabras clave
Data visualization
Information dashboards
Meta-modeling
Software product line
Model-driven development
Clasificación UNESCO
1203 Ciencia de los ordenadores
Fecha de publicación
2022
Citación
Andrea Vázquez-Ingelmo, Francisco José García-Peñalvo, Roberto Therón, MetaViz – A graphical meta-model instantiator for generating information dashboards and visualizations, Journal of King Saud University - Computer and Information Sciences, Volume 34, Issue 10, Part B, 2022, Pages 9977-9990, ISSN 1319-1578, https://doi.org/10.1016/j.jksuci.2022.09.015. (https://www.sciencedirect.com/science/article/pii/S1319157822003445)
Resumen
[EN]This work presents the application of meta-modeling to the data visualization and
dashboards’ domain to obtain two main products: a system that allows the instantiation of the
meta-model through a graphical interface and a code generator that takes the instantiation of the
meta-model as an input to generate visualizations and dashboards.
Methods: A domain engineering approach complemented with an example-driven methodology was iter-
atively employed to develop the dashboard meta-model. This meta-model was subsequently used as an
input to implement a code generator of information dashboards. These two artifacts were finally com-
bined to design and develop the architecture of MetaViz.
Results: Through this process, it was possible to generate visualizations and dashboards using visual ele-
ments and basic interactions. MetaViz allows the generation of basic charts (line charts, scatter plots, pie
charts, etc.) as well as more complex displays with interactive behavior along different views, layouts,
and operations.
Conclusions: The development of MetaViz has served as proof of the viability and benefits of applying
these methodologies to a complex domain, but also to set the foundations of a system that allows users
to trace every single element from a data visualization to its most primitive values.
URI
ISSN
1319-1578
DOI
10.1016/j.jksuci.2022.09.015
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