Subject description - XP39VIZ

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XP39VIZ Advanced Visualization Methods
Roles:S Extent of teaching:2P
Department:13139 Language of teaching:
Guarantors:Čmolík L., Slavík P. Completion:ZK
Lecturers:Čmolík L., Slavík P. Credits:4
Tutors:  Semester:Z


Human factors in visualization (Perception and cognition, Visual saliency, Visual thinking) Design of User Interfaces for Visualization applications (Evaluation of visualization techniques) Advanced volume visualization (Illustrative volume rendering) Big data visualization, Visual analytics, Animation for visualization, Data compression and reduction Large scale data visualization Visualization techniques in nonstandard environment

Study targets:

The goal ofthis course is to acquaint students with up to date methods of visualization where the attention is paid to various fields where visualization may be used. Namely the wide coverage of the applications of visualization can be considered innovative (in comparison with traditional approaches used worldwide up to now).


The course can be considered as a follow up of the visualization course in MSc. study. This linkage allows student who never came across with visualization to get the basic info about visualization and its application. The info acquired can be further developed in the course for PhD students. The main difference in comparison with MSc. course is the stress that is put on the role of human factors in visualization. In further new methods in visualization will be discussed - like big data visualization, data compression, usage of animation in visualization, visualization in non-standard environment etc.). When taking into account the fact that almost in each dissertation some data should be visualized - then each student should be acquainted with relevant visualization methods. This approach should result in much better evaluation of the data processed.

Course outlines:

1.-2.  Human factors in visualization. Perception and cognition. Visual thinking.
3.-4.  Design of user interfaces for visualization applications. Methods for evaluation of visualization techniques.
5.-6.  Advanced methods for volume visualization. Illustrative volume rendering.
7.-8.  Visualization of big data. Visual analytics. Visualization and animation. Data compression.
9.-10.  Visualization of data acquired from various sources (data in mu1timodal environment).
11.-12.  Visualization in non-standard environments (mobile environment, virtual reality etc.]
13.-14.  New trends in data visualization

Exercises outline:

Acquaitance with the goal of seminars. Organization of excercises. Requirements for exam. Semestral project. Consultations to the project. Study and presentation of particular topics in the field of visualization. Final presentation of the project together with evaluation of results reached together with its contribution to dissertation to be.


Tamara Munzer: Visualization Analysis and Design, AK Peters, 2014 Colin Ware: Visual Thinking for Design, Elsevier Inc., 2008 Nathan Yau, Data Points: Visualization that means something That Means Something, Wiley, 2013


It may be beneficial for students to pass course Visualization in MSc. track


human factors; big data; visualization; interface design

Subject is included into these academic programs:

Program Branch Role Recommended semester
DOKP Common courses S
DOKK Common courses S

Page updated 15.6.2024 17:51:22, semester: Z/2024-5, Z,L/2023-4, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)