Subject description - B4M39VIZ

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B4M39VIZ Visualization
Roles:PO Extent of teaching:2P+2C
Department:13139 Language of teaching:CS
Guarantors:Čmolík L. Completion:Z,ZK
Lecturers:Čmolík L., Slavík P. Credits:6
Tutors:Čmolík L., Pavlovec V. Semester:L

Web page:


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 - both in the field of information visualization and scientific visualization as well.

Course outlines:

1. Introduction to visualization
2. Data categorization
3. Principles of data visualization
4. Vizualizace skalárních dat
5. Vizualizace objemových dat
6. Vizualizace vektorových dat
7. Vizualizace n-rozměrných dat
8. Vizualizace relačních dat
9. Text and software visualization
10. Time and its visualization
11. User interface and interaction in visualization
12. Visual data mining, visual analytics, big data
13. Trends in visualization
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. Fayyad, U., Grinstein, G.G., Wierse, A.: Information Visualization in Data Mining and Knowledge Discovery, Morgan Kaufmann, 2002
2. Stasko,J., Domingue,J., Brown,M.H., Price, B.A.: Software Visualization, MIT Press, 1998
3. Chen, Ch.: Information Visualization and Virtual Environments,Springer, 1999
4. Tamara Munzner. Visualization Analysis and Design. A K Peters Visualization Series, CRC Press, 2014.
5. Alexandru C. Telea. Data Visualization: Principles and Practice (2nd edition). CRC Press, 2014.


Subject related pages:

Subject is included into these academic programs:

Program Branch Role Recommended semester
MPOI3_2018 Computer Graphics PO 2
MPOI9_2018 Data Science PO 2
MPOI1_2018 Human-Computer Interaction PO 2

Page updated 31.3.2023 09:52:03, semester: Z/2023-4, Z/2024-5, Z,L/2022-3, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)