Information visualization tools are widely used to better understand
large and complex datasets. However, to make the most out of them,
it is necessary to rely on proper designs that consider not only the
data to be displayed, but also the audience and the context. There are
tools that already allow users to configure their displays without
requiring programming skills, but this research project aims at
exploring the automatic generation of information visualizations
and dashboards in order to avoid the configuration process, and
select the most suitable features of these tools taking into account
their contexts. To address this problem, a domain engineering, and
machine learning approach is proposed.
