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Título
Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards
Autor(es)
Materia
Information dashboards
Metamodeling
Visualization goals
Visualization tasks
Data visualization
Educational dashboards
Clasificación UNESCO
1203.17 Informática
Fecha de publicación
2020
Resumen
[EN]Information dashboards are everywhere. They support knowledge discovery in a huge
variety of contexts and domains. Although powerful, these tools can be complex, not only for the
end-users but also for developers and designers. Information dashboards encode complex datasets
into different visual marks to ease knowledge discovery. Choosing a wrong design could
compromise the entire dashboard’s effectiveness, selecting the appropriate encoding or
configuration for each potential context, user, or data domain is a crucial task. For these reasons,
there is a necessity to automatize the recommendation of visualizations and dashboard
configurations to deliver tools adapted to their context. Recommendations can be based on different
aspects, such as user characteristics, the data domain, or the goals and tasks that will be achieved or
carried out through the visualizations. This work presents a dashboard meta-model that abstracts
all these factors and the integration of a visualization task taxonomy to account for the different
actions that can be performed with information dashboards. This meta-model has been used to
design a domain specific language to specify dashboards requirements in a structured way. The
ultimate goal is to obtain a dashboard generation pipeline to deliver dashboards adapted to any
context, such as the educational context, in which a lot of data are generated, and there are several
actors involved (students, teachers, managers, etc.) that would want to reach different insights
regarding their learning performance or learning methodologies.
URI
DOI
10.3390/app10072306
Versión del editor
Colecciones
- GRIAL. Artículos [441]