Course Visualization

The first part of this course presents fundamental and advanced information visualization techniques for multi-dimensional and hierarchical data, graphs, time-series data, cartographic and categorical data. During the second half, algorithms and models for the scientific visualization of volumetric and vector-based data as well as corresponding out-of-core and level-of-detail techniques for handling very large datasets are introduced.

Various approaches presented in lectures will be studied, in part practically through labs and assignments, and with case studies. Lab classes focus on implementing, testing and evaluating the visualization approaches presented during the lectures. This course will be taught in English.

• Due to the C19 situation the whole course will be held online in Moodle.
  

The documents from last year serve as a basis and will be further developed. The video material and the lecture pdfs (Adobe reader works best) are only available for your personal use! By downloading the material you agree that you do not further distribute it. The pdf files are only available from within the university network or through vpn.

• Introduction (7. May 2020) (see also Munzner's book for exam preparation)
• Visual Encoding (14. May 2020) (see also Munzner's book for exam preparation)
• Manipulate - Facet - Reduce (14. May 2020) (see also Munzner's book for exam preparation)
  • Video Eureka
  • Video Film Finder
• Multi-Attribute Visualization (21. May 2019)
  
  • Video Influence Explorer
  • Video Prosection Matrix
  • Video Scatter Dice
• Glyphs (no lecture, pdf only, not part of the exam)
• Parallel Coordinates (28. May 2020)
  
  • Product Explorer
• Set Visualization (4. June 2020)
• Time Series (11. June 2020)
• Introduction to Scientific Visualization (18. June 2020)
• Color Maps, Contours and Iso-Surfaces (25. June 2020)
• Advanced Volume Rendering (2. July 2020)
• Volume Rendering Optimizations (2. July 2020)
  
• Multi-Resolution Volume Rendering (9. July 2020)
• Trees (16. July 2020)
• Graphs and Networks (16. July 2020)
  • Video Sunburst
  • Video Gnutella
  • Interactive Sankey Diagrams
• Text and Document Visualization (23. July 2020)

• Munzner: Visualization Analysis and Design
• Tominski, Schumann: Interactive Visual Data Analysis
• Heer, Bostock, Ogievetsky: A Tour through the Visualization Zoo
• Ware: Information Visualization - Perception for Design
  

• Grading Information
  • The following scheme lists the grades depending on the percentage of the achieved points in the lab class:
    • 1.0   >=95.0
    • 1.1   [93.5-95.0)
    • 1.2   [92.0-93.5)
    • 1.3   [90.5-92.0)
    • 1.4   [89.0-90.5)
    • 1.5   [87.5-89.0)
    • 1.6   [86.0-87.5)
    • 1.7   [84.5-86.0)
    • 1.8   [83.0-84.5)
    • 1.9   [81.5-83.0)
    • 2.0   [80.0-81.5)
    • 2.1   [78.5-80.0)
    • 2.2   [77.0-78.5)
    • 2.3   [75.5-77.0)
    • 2.4   [74.0-75.5)
    • 2.5   [72.5-74.0)
    • ...
    • 3.0   [65.0-66.5)
    • ...
    • 4.0   [50.0-51.5)
    • Less than 50% is insufficient for an admission to the exam.
• Contributions to the final grade
  • lab class assignments: 50%
    • InfoVis: 70%
    • SciVis: 30%
  • exam: 50%
  • final project (optional for 6 ECTS)
    • the course grade and the grade for the final project will be combined based on the respective ECTS