Overview of methods and fundamentals in the field of visual representation of big data. Students understand the basic concepts, know application areas and develop an implementation project.

Fundamentals of Computer Science (inf-01), Practical Computer Science (inf-02)

The following topics will be covered in the course:

• Results for target audience (Perception / Cognition)
• Augmented Visualization
• Medical Visualization
• Scientific Visualization
• Visual Analyticals
• "Storytelling"

The following basic literature will be used in the course:

• Simon P,: "The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions", John Wiley & Sons, Inc. , 1st edition, 2014;
• Miller J.D.: "Big Data Visualization", Packt Publishing, 1st edition, 2017;
• Rahlf T.: "Data Design with R - 100 Visualization Examples", Open Source Press, 1st edition, 2014;
• Brath R., Jonker D. "Graph Analysis and Visualization: Discovering Business Opportunity in Linked Data", John Wiley & Sons, 1st edition, 2015;

Lecture, group work, guest lecturers, interactive teaching.

Final grade comprised of

• Class participation
• Discussion
• Partial tests (continuous assessment)