Lecture Course: Data Visualization, Summer Term 2021

Goals

To become familiar with the basic concepts and algorithms used in the field of visualization. The students should be able to visualize abstract and spatial data in a way that enhances our perception of the desired relationships in the underlying data. In addition, the students should be able to implement a wide range of visualization techniques in existing frameworks or even to design and implement them from the ground up.

Content

The students will be taught the basics in the areas of Information Visualization (INFOVIS) and Scientific Visualization (SCIVIS). The different techniques in the context of the visualization pipeline are covered, which serves as a red thread for the course. The main focus is on interactive visualization techniques that allows the user for example to interact with the visualizations in order to filter the data being displayed or to change display parameters. The course covers the following topics:

  • Overview
  • The visualization pipeline
  • Data structures for spatial data 
  • Visualization of scalar, vector and tensor fields
  • Visualization of multi-parametric data
  • Glyph based techniques
  • Key aspects of visual perception
  • Applications of modern visualization systems

Exercise Lessons

The exercise lessons will be held in parallel to the lecture course.