Subject description - BE4M39VIZ

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BE4M39VIZ Visualization
Roles:PO Extent of teaching:2P+2C
Department:13139 Language of teaching:EN
Guarantors:Čmolík L. Completion:Z,ZK
Lecturers:Čmolík L. Credits:6
Tutors:Čmolík L., Pavlovec V. Semester:L

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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:

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 outline:

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


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.


Subject is included into these academic programs:

Program Branch Role Recommended semester
MEOI1_2018 Human-Computer Interaction PO 2
MEOI9_2018 Data Science PO 2
MEOI3_2018 Computer Graphics PO 2

Page updated 19.5.2024 07:51:08, semester: Z,L/2023-4, Z/2024-5, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)