Data visualization aims at providing people insight into large amounts of data using interactive computer graphics by exploiting the unique capabilities of the human visual system to perceive patterns, trends, and outliers. The course aims to provide a broad overview of data visualization and to engage students via hands-on exercises.
This graduate course is intended for Ph.D. students that are interested in data visualization and use it or want to use it for their research.
The first day an overview is provided via a number of lectures, followed by four days in which specific topics are addressed via hands-on exercises. The topics are:
- Information visualization: visualization of abstract data, such as tables, hierarchies, networks, and combinations thereof;
- Visual analytics: the use of a combination of automated analysis and interactive visualization, for instance to analyze large multi-media collections;
- Scientific visualization: visualization of data with a geometric component, for instance visualization for medical applications.
- Hardware acceleration: the use of GPU-shaders to obtain special effects in real-time.