For a general description about research in Visual Analytics please see here at the overview page.

Data Quality

Poor data quality leads to unreliable results of any kind of data processing and has profound economic impact. Although there are tools to help users with the task of data cleansing, support for dealing with the specifics of time-oriented data is rather poor. However, the time dimension has very specific characteristics which introduce quality problems, that are different from other kinds of data. To this end we tackle this important topic with Visual Analytics methods.

Data quality control can be divided into

Visual Analytics of Large Homogeneous Data

Homogeneous multivariate data encompass multiple variables that have the same semantics. As example, these variables can represent the probabilities for a sample to belong to different classes, or item memberships of multiple sets.

With a large number of items, such homogeneous data tables become very rich of information that explains how the row entities are related to the different column variables, and how the columns are related to each other according to their relationships with the rows.

Visual Debugging

Advanced debuggers available in modern IDEs make it easier to debug programs and understand their runtime behavior. In this project we aim to enrich software debuggers in popular Java IDEs with visual methods that provide more insight into information available at the runtime. Example for this information are traces collected at tracepoints set by the user, the values of the variables over time, or values in large arrays.

Science of Interaction

Visual Analytics strongly emphasizes the importance of interaction. However, until now, interaction is only sparingly treated as subject matter on its own. How and why interactivity is beneficial to gain insight and make decisions is mostly left in the dark. Due to this lack of initial direction, it seems important to make further attempts in facilitating a deeper understanding of the concept of interactivity. Therefore, different perspectives towards interactivity as well as cognitive theories and models are investigated.


In this project we support medical experts in exploring patients' conditions as well as the effects of clinical actions on patients' conditions.