After successful completion of the course, students are able to describe the theoretical concepts applied in information visualization and presented in the lecture (e.g., visualization of multimdimensional data, visualization of multivariate network data).
Information visualization is "the use of computer-supported, interactive, visual representations of abstract data to amplify cognition". The participants shall get acquainted to the concepts and techniques of information visualization. A short general introduction to visualization is followed by presentations of current research results in the field. The topics include:
- Data & Visual Encodings
- Visual & Perceptual Principles
- Multivariate & High-Dimensional Data Visualization
- Multivariate Network Visualization
- Scalable Visualization for Big Data
- Explainable AI
- Applications of visualization, e.g., for biology or engineering
There is an exercise accompanying the lecture.
Didactical Approach: With slides, an introduction to information visualization is given. (International) colleagues give guest lectures concerning current special topics.
Zoom links to the lectures, lecture recordings, and all lecture materials can be found on TUWEL. Lectures take place Wednesdays 3 p.m. (c.t.).
After the introductory part, there will be a 15 minutes open book exam in TUWEL (30 points). At the end of the lecture, there will be an oral exam via Zoom (70 points). For the oral exam, students need an audio- and video connection via Zoom. Both exams have to be positive (i.e., > 50% of the points) for a positive grade.
