Module Handbook

  • Dynamischer Default-Fachbereich geändert auf INF

Course INF-19-51-K-6

Visual Analytics (2V+2U, 5.0 LP)

Course Type

SWS Type Course Form CP (Effort) Presence-Time / Self-Study
- K Lecture with exercise classes (V/U) 5.0 CP 94 h
2 V Lecture 28 h
2 U Exercise class (in small groups) 28 h
(2V+2U) 5.0 CP 56 h 94 h


CP, Effort 5.0 CP = 150 h
Position of the semester 1 Sem. in SuSe
Level [6] Master (General)
Language [DE/EN] German or English as required
Area of study [INF-VIS] Visualisation and Scientific Computing
Livecycle-State [NORM] Active

Possible Study achievement

  • Verification of study performance: proof of successful participation in the exercise classes (ungraded)
  • Details of the examination (type, duration, criteria) will be announced at the beginning of the course.


  • formal foundation
    • basic terms of visual data analysis
    • modular components of a visual analytics system
    • common data sources and their processing
    • mathematical concepts of data analysis
    • visualization concepts for complex systems
    • integration of automated and visual analysis procedures
  • analysis of classified data
    • classifiers
    • information theory to quantify the information content
    • VA strategies for analysis, exploration and editing of classification algorithms
  • analysis of time-dependent data
    • characteristics of time dependent data
    • visualization concepts and algorithms for time-dependent data
    • discussion of the supported time characteristics and analysis options
  • analysis of high-dimensional data
    • animation techniques for projection processes
    • distance dimensions for high-dimensional data
    • non-linear projection method
    • VA for evaluation and analysis of projection methods
    • cluster methods and their analysis
  • topological methods in the VA


  • Illuminating the Path edited by J. Thomas and K. Cook, IEEE Press, 2006.
  • Ward, Matthew O., Georges Grinstein, and Daniel Keim. Interactive data visualization: foundations, techniques, and applications. CRC Press, 2010.
  • Dill, John, et al., eds. Expanding the Frontiers of Visual Analytics and Visualization. Springer Science & Business Media, 2012.

Requirements for attendance (informal)


Requirements for attendance (formal)


References to Course [INF-19-51-K-6]

Module Name Context
[INF-19-51-M-6] Visual Analytics P: Obligatory 2V+2U, 5.0 LP
Course-Pool Name
[INF-VIS_V-KPOOL-6] Lectures of the teaching area Visualization and Scientific Computing