Information Visualization

A list of potential topics for PhD students in the area of Information Visualization.

Interactive Network Visualization

Supervisor:  Benjamin Bach

This PhD topic investigates interactive and visual means to better understand complex network data. Visualization allows to understand information otherwise hidden in data, statistics or mathematical models. Visualization is a powerful means to understand complexity, to create hypotheses and to inform further research. As no visualization is able to capture the entire picture, interactive exploration and manipulation of the visualization can further support an analysts workflow. The goal of this thesis is to create novel information visualization and interaction techniques to help people understand network and relational data.

More about Interactive Network Visualisation

 

Visualization Tools for Open Science

Supervisor:  Benjamin Bach

Open science relies on sharing, annotating, discussing, and communicating information, ideally across domain boundaries. (Interactive) visualizations can play a crucial role in presenting data and making data accessible beyond the rather static figures in PDF documents. Visualizations for open science require custom tools and platforms that support publication of interactive material (e.g., visualization, analysis notebooks) as well as supporting function for versioning, discussion, and linking.

This project wants build interfaces and tools to provide a large range of scholars from different domains (biologists, digital humanities, computer science, etc...) with the power to publish, communicate, and to have a larger audience engaging in their data. What tools are necessary? How can they these interfaces made understandable to an audience of huge variety? Which role do interactive visualizations play? Which visualization tools are best suited for publication on the web, in PDFs? Which formats and tools are required by scientists to publish and present their data?

 

Interactive Data Visualization for Immersive Augmented Reality (in Biology)

Supervisor:  Benjamin Bach

The latest generation of augmented reality (AR) display-technology has reached a level of consumer-readiness, including head-mounted and stereoscopic display (e.g. Microsoft HoloLens), as well as developer support. This technology is of interest in the visualization of 3D-networks of biological data such as, derived from gene expression measures, chromatin structures, and brain-connectivity networks.  Besides an improved perception of depth, immersive augmented reality will likely benefit collaboration and interaction with existing display and interaction technologies (projectors, screens, mouse, keyboard). The main question is how these technologies can play well together in order to support a seamless workflow and improved analytical paradigm.

In particular, this project will investigate creative approaches to support workflows around biological data, using a hybrid setup of screen and holograms (Microsoft HoloLens). Which data needs to be visualized as hologram? How to interact with holograms? How to visualize that data? Which data is to be shown on the screen? How to couple both environments to provide for a smooth workflow?