Spring Semester 2010


Feb 05: First homework assignment is due on Feb 18, before the class. You can send me your Amira files by email and give me the paperwork before the class.

Jan 21: The first lecture and the software tools are online. If possible, please install the tools until next week.

Jan 17: Details about the course are online.

This page will be updated during the semester.


Large amounts of data are produced every day in a variety of domains such as engineering, medicine, natural sciences, or meteorology. Due to the ever increasing size and complexity of simulated and measured data, its analysis becomes more challenging. A successful approach to this is data visualization, i.e., the creation of images or videos which allow for a fast and intuitive identification of the most important properties inherent to the data.

See some visualizations for yourself (these videos have been created with Amira by me and my colleagues at Zuse Institute Berlin):

The course gives an overview of the most important approaches to data visualization and discusses their advantages and limits. The necessary mathematical tools will be presented along the way (these include topics in numerical mathematics and topology). A state-of-the-art visualization system will be used to examine real-world data sets coming from the fields of medicine and fluid dynamics.

Covered topics:

Expected Work

The course is suitable for advanced MS students and PhD students. Students will analyze, visualize, and interpret data sets from different domains using a state-of-the-art visualization system. Familiarity with basic computer graphics (or motivation to learn this fast) is desirable. Assessment will be based on several homework assignments, a paper presentation and a course project.

Structure of the Course

Every session will consist of two parts:

Homework Assignments

Typical assignments consist of a small number of problems that you are supposed to solve in order to deepen your understanding of the presented algorithms and techniques. I will hand out 5 such assignments. They will not only consist of theoretical questions, but some practical work with a visualization tool will be required as well. Estimated required time to solve a homework assignment is 2 hours.

There are two special homework assignments, that are special in the sense that they do not follow the typical question-answer scheme. Another special facet about them is that I have to do them, too. ;-) Here they are:

Course Project

The course project will be a visualization of a large and complex data set. You have to choose the right tools to uncover the hidden structures in the data set. You write a webpage incorporating your visualization images and videos, where you explain your choice of visualization techniques and interpret your results.

The following data sets are available for this:

You have to decide on a data set before spring break.



The schedule is tentative and may be adjusted along the way.


Introduction, administrativa.

Problem description, history, the visualization pipeline, visualization scenarios, applications


data description, interpolation, selection


Mapping of characteristics of a data set to graphical primitives and attributes


Visualization of multiparameter data, parallel coordinates.


Volume visualization, volume rendering, part I.


Volume visualization, volume rendering, part II.


Flow visualization, part I: concepts, direct and geometric visualization techniques


Flow visualization, part II: texture-based methods


Spring break


Feature-based methods for scalar and flow visualization, Identification of vortices in flows


Topology of scalar and vector fields in static and time-dependent data sets, Applications of topological methods


Top Scientific Visualization Research Problems, Tensor visualization, DT-MRI data


Information visualization


The Value of Visualization, Music visualization, Video visualization, Software visualization


Summary, demos, end-of-term party :-)