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Visualization

(in German: Visualization )

Module-ID: FIN-INF-102812
Link: LSF
Responsibility: Bernhard Preim
Lecturer: Bernhard Preim
Classes:
  • Lecture Visualization
  • Exercise Visualization
 
Applicability in curriculum: - B.Sc. INF: Informatik - Wahlpflicht
- B.Sc. CV: Computervisualistik - Pflicht
- B.Sc. INGINF: Informatik - Wahlpflicht
- B.Sc. WIF: Gestalten und Anwenden - Wahlpflicht
- B.Sc. INF (bilingual): Informatik - Wahlpflicht

Abbreviation

VIS

Credit Points

5

Semester

Winter

Term

Duration

1 Semester

Language

english

Level

Bachelor

Intended learning outcomes:
Students ...

  • understand how physiological perception affects visualization effectiveness
  • know basic visualization techniques, such as color coding, diagramme types and techniques to visualize graph and network data
  • can generate appropriate visualizations for business and statistical data

Content:

  • Visualization goals and quality criteria
  • Understanding of fundamentals of visual perception
  • Overview of data structures in visualization
  • Basic algorithms (Isolines, color scales, diagramm techniques),
  • Direct and indirect visualization of volume data
  • map-based visualization
  • dashboard design
  • Information visualization

Workload:
56 contact hours + 94 h self study

Pre-examination requirements: Type of examination: Teaching method / lecture hours per week (SWS):

Successful participation in the exercise (voting system, vote for at least 2/3 of all tasks)

Written exam

  • 2 SWS Lectures
  • 2 SWS Exercise classes
Prerequisites according to examination regulations: Recommended prerequisites:

none

  • Module: Computer Graphics I
Media: Literature:

  • Powerpoint presentation
  • Sketches
  • Videos

  • P. and M. Keller (1994): Visual Cues, IEEE Computer Society PressT. Munzner (2015). Visualization Analysis and Design: Principles, Techniques, and Practice, A K Peters
  • W. Schroeder, K. Martin, B. Lorensen (2001): The Visualization Toolkit: An object-oriented approach to 3d graphics, 3. Aufl. Springer, Heidelberg
  • A. Telea (2014): Data Visualization: Principles and Practice, Second Edition, AK Peters (2. Auflage)
  • Munzner, T. (2014). Visualization analysis and design. CRC press.
  • Tominski, C., & Schumann, H. (2020). Interactive visual data analysis. AK Peters/CRC Press.
  • M. Ward, D. Keim, G. Grinstein (2015): Interactive Data Visualization: Foundations, Techniques, and Applications, Second Edition

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