FI:PA214 Visualization II - Course Information
PA214 Visualization IIFaculty of Informatics
- 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
- Tue 15. 2. to Tue 10. 5. Tue 12:00–13:50 S108
- Timetable of Seminar Groups:
PA214/02: Tue 22. 2. to Tue 3. 5. each even Tuesday 10:00–11:50 S108, J. Byška, K. Furmanová, V. Rusňák
PA214/03: Tue 15. 2. to Tue 10. 5. each odd Tuesday 14:00–15:50 S108, J. Byška, K. Furmanová, V. Rusňák
PA214/04: Tue 22. 2. to Tue 3. 5. each even Tuesday 14:00–15:50 S108, J. Byška, K. Furmanová, V. Rusňák
- 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
- Study Materials
The course is taught annually.