1. Introduction to the topic

2. Visual perception, visual representation of data, Gestalt principles, information overload

3. Creating visual representations, visualization reference model, visual mapping, visual analytics

4. Design of visualization techniques, architecture of visualization systems, design patterns for visualization systems

5. Classification of visualization systems 6. Interaction and distortion techniques

7. Visualization of one-, two- and multi-dimensional data, text and text documents

8. Visualization of groups, trees, graphs, clusters, networks, software 9. Metaphorical visualization

10. Visualization of volumetric data, vector fields, processes and simulations

11. Visualization of maps, geographic information, GIS systems 12. Collaborative visualizations

13. Evaluating visualizations.

Type of methodology: Combination of lecture and hands-on

Participants receive the certificate of attendance: Yes

Paid training activity for participants: Yes, for all

Participants prerequisite knowledge: Numerical methods (linear algebra, statistics) Domain-specific background knowledge