PA214 Visualization II

Faculty of Informatics
Spring 2023
Extent and Intensity
2/0/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught in person.
RNDr. Jan Byška, Ph.D. (lecturer)
RNDr. Katarína Furmanová, Ph.D. (lecturer)
doc. RNDr. Barbora Kozlíková, Ph.D. (lecturer)
RNDr. Vít Rusňák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Barbora Kozlíková, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
PV251 Visualization
Knowledge of basic visualization principles and techniques, taught in the PV251 Visualization I course.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 29 fields of study the course is directly associated with, display
Course objectives
The course should extend the knowledge of students in visualization and its specific usage in different domains. The students will understand the principles of the main visualization disciplines - information visualization, scientific visualization, and visual analysis. These will be demonstrated on real application scenarios from different fields - medical, molecular, environmental visualization, etc.
By presenting and analyzing the latest papers in this field, the students will obtain a solid overview of the current research topics in visualization.
Learning outcomes
- Knowledge of the principles of information visualization, scientific visualization, and visual analysis
- Overview of the application domains and domain-specific tasks and problems, capability to analyze these problems
- Understanding research papers in visualization
- Capability to complete own visualization project - from initial data and problem analysis to the design of a solution and final implementation.
  • Visualization - main topics and challenges (summarizing the basic information about visualization)
  • Visualization process - from analysis and design to realization
  • Information visualization principles and examples
  • Scientific visualization principles and examples
  • Visual analysis (VA) principles and examples
  • Medical and molecular visualization and VA
  • Environmental and geovisualization and VA
  • Volumetric visualization and VA
    recommended literature
  • MUNZNER, Tamara. Visualization analysis & design. Illustrated by Eamonn Maguire. Boca Raton: CRC Press, Taylor & Francis Group, 2015. xxiii, 404. ISBN 9781466508910. info
Teaching methods
The lectures will consist of lectures and invited talks, given by visualization experts from these fields. In the seminar, the students will work on their own visualization project.
Assessment methods
The student's evaluation will consist of the project and written exam.
Language of instruction
Further Comments
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Spring 2020, Spring 2021, Spring 2022.
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