Data Visualization

Course Description

Introduction to data visualisation. The purpose and principles of data visualisation. What, how and why to visualise data. Basic visualisation techniques and tools. Visualisation of univariate, bivariate and multivariate data. Visualisation of temporal, hierarchical, textual and geo-spatial data. Visualisation of linked data, trees, graphs and networks.

Learning Outcomes

  1. explain the basic elements of a data visualization
  2. propose the design of a data visualisation
  3. create an effective data visualisation using appropriate tools
  4. critically assess the design of a data visualisation

Forms of Teaching

Lectures

The classes are organized in two blocks: The first block comprises 7 classes and a midterm exam, while the second comprises 6 classes and a final exam. this makes in total 15 weeks with 2 hours per week.

Independent assignments

Students need to resolve independently practical tasks as preparation for laboratory exercises.

Laboratory

During the laboratory exercises, students work on cleaning, exploratory analysis and visualization of different types of data using different software frameworks for data visualization.

Week by Week Schedule

  1. Data and image models
  2. Graphical perception
  3. Visual coding
  4. Color, animation, interaction
  5. Visualization toolkits
  6. Multivariate data visualization
  7. Multivariate data visualization
  8. Midterm exam
  9. Temporal data visualization
  10. Hierarchical data visualization
  11. Textual data visualization
  12. Geo-spatial data visualization
  13. Graph and tree visualizations
  14. Network and linked data visualization
  15. Final exam

Study Programmes

University graduate
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Literature

Edward R. Tufte (2001.), The visual display of quantitative information, 2nd ed., Graphics
Kristen Sosulski (2018.), Data Visualization Made Simple: Insights Into Becoming Visual, Routledge
Leland Wilkinson (2005.), The grammar of graphics, Springer
Hadley Wickham (2016.), ggplot2: Elegant Graphics for Data Analysis, Springer
Tamara Munzner (2014.), Visualization Analysis and Design, CRC Press

For students

General

ID 223735
  Winter semester
5 ECTS
L1 English Level
L1 e-Learning
30 Lectures
0 Seminar
0 Exercises
12 Laboratory exercises
0 Project laboratory

Grading System

Excellent
Very Good
Good
Acceptable