Visualization

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Faculty of Information Technology

Synopsis:

In this course, you will get the knowledge of theoretical background

for visualization and the application of visualization in real-world

examples. The visualization methods are aimed at exploiting both the

full power of computer technologies and the characteristics (and

limits) of human perception. Well-chosen visualization method serves as an external representation, with which it is possible to quickly obtain data values or compare data. This frees up the memory and cognitive capabilities of the analyst to solve the problem that the data represents.

Requirements:

Syllabus of lectures:

1. Introduction to visualization

2. Data and task categorization

3. Principles of data visualization

4. Interaction in visualization

5. Visualization of scalar fields

6. Visualization of volumetric data

7. Visualization of vector fields

8. Visualization of tabular data

9. Visualization of multidimensional data, text visualization

10. Visualization of relational data

11. Visualization of geographic data

12. Time and its visualization

13. Visual analytics, big data, visual data mining

14. Spare lecture

Syllabus of tutorials:

1. Introduction to the course

2. Introduction to Paraview

3. Data mapping in Tableau Public

4. Consultations of semestral works

5. Visualization of scalar fields

6. Visualization of volumetric data

7. Visualization of vector fields

8. 1st test

9. Consultations of semestral works

10. Visualization of n-dimensional data

11. Visualization of relational data

12. 2nd test

13. Presentations of semestral works

14. Spare seminar

Study Objective:

To master basic methods and tools for data visualization - in the fields of scientific visualization and information visualization.

Study materials:

1. Tamara Munzner: Visualization Analysis and Design. A K Peters Visualization Series. CRC Press, 2014. ISBN 978-1466508910.

2. Alexandru C. Telea: Data Visualization: Principles and Practice (2nd edition). CRC Press, 2014. ISBN 978-1466585263.

Note:

Further information:

https://moodle.fel.cvut.cz/course/B4M39VIZ

No time-table has been prepared for this course

The course is a part of the following study plans:

• Quantum Informatics (elective course)
• Mgr. programe Applied informatics (code ANIE) for the phase of study without specialization (VO)
• Master specialization Embedded systems (VO)
• Master specialization Business Informatics, 2026 (VO)
• Master specialization Software Engineering (VO)
• Master specialization Web Engineering (VO)
• Master specialization Visual computing and Game design (PS)
• Master specialization Computer Security, in Czech, 2026 (elective course)
• Master specialization Computer Systems and Networks, in Czech, 2026 (elective course)
• Master specialization Computer Science, in Czech, 2026 (elective course)
• Master specialization Programming Languages, in Czech, 2026 (elective course)
• Master specialization Artificial Intelligence, in Czech, 2026 (elective course)
• Master programme, for the phase of study without specialisation, ver. for 2026 and higher (elective course)