Visualization

B252 - Summer 25/26

This is a grouped Moodle course. It consists of several separate courses that share learning materials, assignments, tests etc. Below you can see information about the individual courses that make up this Moodle course.

B4M39VIZ BE4M39VIZ

Visualization - B4M39VIZ

Main course

Credits	6
Semesters	Summer
Completion	Assessment + Examination
Language of teaching	Czech
Extent of teaching	2P+2C

Annotation

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.

Study targets

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

Course outlines

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 relational data
10. Text and software visualization
11. Visualization of geographic data
12. Time and its visualization
13. Visual data mining, visual analytics, big data
14. Spare lecture

Exercises outlines

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

Literature

1. Tamara Munzner. Visualization Analysis and Design. A K Peters Visualization Series, CRC Press, 2014.

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

Requirements

None

Visualization - BE4M39VIZ

Credits	6
Semesters	Summer
Completion	Assessment + Examination
Language of teaching	English
Extent of teaching	2P+2C

Annotation

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 methods can help to reveal hidden dependencies in the data that are not evident at the first glance. This in turn enables a more precise analysis of the data or provides a deeper insight into the core of the particular problem represented by the data.

Study targets

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

Course outlines

Exercises outlines

1. Introduction to the course
2. Introduction to Paraview
3. Introduction to Tableau Public
4. Visualization of scalar data
5. Visualization of volumetric data
6. Visualization of vector data
7. 1st test
8. Presentations of STAR reports
9. Visualization of n-dimensional data
10. Visualization of relational data
11. 2nd test
12. Visual analytics
13. Presentations of semestral works
14. Spare seminar

Literature

Requirements

None