PV251 Visualization

Faculty of Informatics
Autumn 2025
Extent and Intensity
2/1/0. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
In-person direct teaching
Teacher(s)
doc. RNDr. Barbora Kozlíková, Ph.D. (lecturer)
RNDr. Katarína Furmanová, Ph.D. (seminar tutor)
Mgr. Adam Rychlý (assistant)
Guaranteed by
doc. RNDr. Barbora Kozlíková, Ph.D.
Department of Visual Computing – Faculty of Informatics
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Wed 17. 9. to Wed 17. 12. Wed 8:00–9:50 A217
  • Timetable of Seminar Groups:
PV251/01: Fri 19. 9. to Fri 12. 12. each even Friday 12:00–13:50 A215, K. Furmanová
PV251/02: Fri 26. 9. to Fri 19. 12. each odd Friday 12:00–13:50 A215, K. Furmanová
PV251/03: Wed 17. 9. to Wed 10. 12. each even Wednesday 10:00–11:50 A215, K. Furmanová
PV251/04: Wed 24. 9. to Wed 17. 12. each odd Wednesday 10:00–11:50 A215, K. Furmanová
PV251/05: Thu 2. 10. 8:00–9:50 C119, Thu 9. 10. 8:00–9:50 C119, Thu 23. 10. 8:00–9:50 C119, Thu 6. 11. 8:00–9:50 C119, Thu 20. 11. 8:00–9:50 C119, Thu 4. 12. 8:00–9:50 C119, K. Furmanová, B. Kozlíková, rezervní skupina
PV251/06: Thu 2. 10. 10:00–11:50 C119, Thu 9. 10. 10:00–11:50 C119, Thu 23. 10. 10:00–11:50 C119, Thu 6. 11. 10:00–11:50 C119, Thu 20. 11. 10:00–11:50 C119, Thu 4. 12. 10:00–11:50 C119, K. Furmanová, B. Kozlíková
Prerequisites
No additional prerequisites.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 60 student(s).
Current registration and enrolment status: enrolled: 86/60, only registered: 4/60, only registered with preference (fields directly associated with the programme): 1/60
fields of study / plans the course is directly associated with
there are 13 fields of study the course is directly associated with, display
Abstract
The goal is to provide students with the overview of the field of visualization and its principles and methods. The course includes basic concepts of visualization and its application to different input data sets. Students also will be acquainted with various interaction techniques for data manipulation and with practical applications of visualization, such as in medicine, art etc. An important part of this course contains practical exercises performed on various visualization tools. At the end of this course, students should be able to design and develop their own effective visualizations.
Learning outcomes
After passing this course, the students will be able to: - evaluate the suitability of existing visualization techniques for a given task - determine the basic mistakes of existing visualization solutions - design appropriate visualizations for given tasks - implement an optimized solution of a selected visualization
Key topics
  • Introduction, history of visualization, visualization today, human perception and information processing
  • Color, types of input data
  • Visualization foundations
  • Visualization techniques for spatial data
  • Visualization techniques for geospatial data
  • Visualization techniques for multivariate data
  • Graphs and trees, networks
  • Text and document visualization
  • Interaction concepts and techniques
  • Designing effective visualizations, comparing and evaluating visualization techniques
  • Visualization tools and systems
  • Specific applications of visualization - medical visualization, NPR, scientific visualization
Study resources and literature
    recommended literature
  • WARD, Matthew; Georges G. GRINSTEIN and Daniel KEIM. Interactive data visualization : foundations, techniques, and applications. Natick: A K Peters, 2010, xvii, 496. ISBN 9781568814735. info
Approaches, practices, and methods used in teaching
Theoretical lectures covering fundamentals, methods, and algorithms for visualization. Lab work focused on usage of various visualization tools and design of visualizations. Short HW assignments demonstrating usage of methods discussed in lectures. Study materials: Slides, study materials and lectures video, textbooks, and journals on visualization.
Method of verifying learning outcomes and course completion requirements
Homework assignments must be completed before the final examination. The final assessment is based on the result of the written exam which consists of 5 theoretical as well as practical questions.
Language of instruction
English
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2025/PV251