I853 – Information Visualization

Module
Information Visualization
Information Visualization

Please note: This module will be offered for the first time in the Summer semester 2025 semester.
Module number
I853
Version: 1
Faculty
Informatics/Mathematics
Level
Master
Duration
1 Semester
Semester
Summer semester
Module supervisor

Prof. Dr.-Ing. Dietrich Kammer
dietrich.kammer(at)htw-dresden.de

Lecturer(s)

Prof. Dr.-Ing. Dietrich Kammer
dietrich.kammer(at)htw-dresden.de

Course language(s)

English
in "Information Visualization"

ECTS credits

5.00 credits

Workload

150 hours

Courses

4.00 SCH (1.00 SCH Lecture | 3.00 SCH Internship)

Self-study time

90.00 hours

Pre-examination(s)
None
Examination(s)

Alternative examination - Semesterarbeit
Module examination | Weighting: 100% | tested in English language
in "Information Visualization"

Form of teaching

Combination of lectures, discussions, and hands-on projects. This includes self-study and the presentation of projects.

Media type

Slides, tutorials, and online resources.

Instruction content/structure

This module is designed to introduce students to the principles and practices of visualizing data and information. Through a combination of lectures, discussions, and hands-on projects, students will gain practical experience using visualization tools and techniques to analyze and present data in a clear and effective manner. Students will learn how to create effective visualizations that can be used to explore, analyze, and communicate complex data sets. 

The course covers a range of topics, including the fundamentals of visual perception and cognition, data visualization techniques, and the use of specialized software tools. Students apply their knowledge to real-world data sets and develop their own visualizations. By the end of the course, students will have a deep understanding of the principles of information visualization and will be able to use visualization to effectively communicate data-driven insights. Students will acquire the skills and knowledge needed to create effective visualizations for a variety of applications.

  • Fundamentals: terms and definitions, basic principles, visualization workflow, visual perception
  • Data preparation: acquisition of data, analysis, transformation, exploration
  • Visualization process: visual coding, interactivity, idioms, and best practices
  • Interaction techniques: Focus and context techniques, operating and orienting, filtering and aggregating, coordinating multiple views
  • Design process: visualization goals, design techniques, prototyping, and realization
  • Construction kit with building blocks: elements and layout structures, interaction classes, data structures and attribute types, task taxonomy, visualization patterns and their combinations
  • Tools: generic tools for visualization, program libraries and frameworks-
  • Applications: search interfaces, visualization of graphs and networks, parallel coordinates and Sankey diagrams
  • Validation: analysis of existing applications, evaluation of interactive information visualizations
Qualification objectives
  • Students know basic terms of information visualization and understand the design process.
  • Students can systematically analyze and solve challenges in the visualization of abstract data.
  • Students can design and implement interactive applications for the visualization of information.
  • Students know methods for the evaluation of information visualizations and can design and conduct empirical studies.
Social and personal skills
  • Development of self-competence in project work by managing time, perseverance, curiosity, responsibility for one's own actions as well as appropriate assessment of one's own performance, self-perception and perception by others.
  • Development of social competence through interaction, communication and conflict management. This includes working in small groups, large groups or individually, listening, expressing one's own opinion, giving and accepting feedback.
Special admission requirements
Recommended prerequisites

I928 Applied Programming (Python) oder I320 Programmierung III

Continuation options
Literature
  • Data Visualisation: A Handbook for Data Driven Design, Andy Kirk, Sage Publications, 2016 (ISBN: 978-1-4739-1214-4)
  • Visualization Analysis & Design, Tamara Munzner, CRC Press, 2015 (ISBN: 978-1-4665-0891-0)
  • Design for Information, Isabel Meirelles, Rockport Publishers, 2013 (ISBN: 978-1-59253-806-5)
  • Readings in Information Visualisation: Using Vision to Think, Stuart K. Card, Morgan Kaufmann, 1999 (ISBN: 1-55860-533-9
  • Information Visualization: Perception for Design, Colin Ware, Morgan Kaufmann, 2004 (ISBN: 1-55860-819-2)
Current teaching resources

See literature recommendations, online resources, and scripts, tutorials, and material in OPAL course.

Notes
No information