Theses in this area aim to understand how observers perceive visualization. Using these insides, we then try to find to visualizations can be improved in order to make them more accessible and therefore easier to find answers to given questions or while exploring the data.

Theses in this area aim to visualize various data like for example email-traffic, dynamic graphs, computer networks, social media, or even satellite orbits. These visualizations should then help observers to find answers to given questions or support them while exploring the data.

CHRONOGRAPH is a graph processing platform supporting distributed, event-driven, history-aware computations on dynamic graphs. While the system offers reasonable scalability and supports multiple graph processing models, evolving graphs also introduce inherent complexity, especially when graphs show strong dynamics over time. The ability to understand communication flows in such complex systems requires a visual analytic tool that supports users in tracing events or investigating how vertex behavior in ongoing computations.

In this thesis, we would like to investigate different approaches to visually explore the CHRONOGRAPH platform with a particular focus on anomaly detection in the time domain. The goal would be to implement a real-time capable web-based application which then could be used to illustrate and evaluate the approaches.

This thesis will be done in cooperation with the Institute of Distributed Systems.