Visual data analysis can be envisioned as a collaboration of the user and the computational
system with the aim of completing a given task. Pursuing an effective system‐user …

Visual analytics (VA) is typically applied in scenarios where complex data has to be
analyzed. Unfortunately, there is a natural correlation between the complexity of the data …

A typical problem in Visual Analytics (VA) is that users are highly trained experts in their
application domains, but have mostly no experience in using VA systems. Thus, users often …

In the age of big data, being able to make sense of data is an important key to success.
Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and …

Guidance is an emerging topic in the field of visual analytics. Guidance can support users in
pursuing their analytical goals more efficiently and help in making the analysis successful …

This paper presents an approach for the interactive visualization, exploration and
interpretation of large multivariate time series. Interesting patterns in such datasets usually …

Trust is a fundamental factor in how users engage in interactions with Visual Analytics (VA)
systems. While the importance of building trust to this end has been pointed out in research …

The visual analysis of dynamic networks is a challenging task. In this paper, we introduce a
new approach supporting the discovery of substructures sharing a similar trend over time by …

Guidance in visual analytics aims to support users in accomplishing their analytical goals
and generating insights. Different approaches for guidance are widely adopted in many …

Guidance can support users during the exploration and analysis of complex data. Previous
research focused on characterizing the theoretical aspects of guidance in visual analytics …