TNM111 · 6 credits · Advanced level (A1N) · Datateknik, Datavetenskap, Medieteknik
Information Visualization
Active · next start VT 2027
96%
passed the latest regular sitting
UPG1 · 26 Mar 2026 · 23 students
99%
passed the regular sittings, all sittings over the last 5 years
UPG1 · 133 students
7%
Harder than 7% of courses at advanced level
Compared with 285 courses at the same level, ordinary exams over the last three academic years. 55 students.
Part of 7 programmes
- Master of Science in Computer Science and Engineering
- Master of Science in Information Technology
- Master of Science in Media Technology and Engineering
- Master of Science in Computer Science and Software Engineering
- Master of Science in Applied Physics and Electrical Engineering - International
- Master of Science in Applied Physics and Electrical Engineering
- Master's Programme in Computer Science
Hand-in or lab
UPG1 Assignments with oral and written presentations
- G
- U
Main rounds
99% passed · 133 students
- 96%23
- 100%32
- 100%43
- 100%35
Later rounds
No sittings with at least 5 students.
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Other module
MUN1 Oral examination
- 5
- 4
- 3
- U
Main rounds
96% passed · 96 students
- 100%21
- 88%32
- 100%43
Later rounds
100% passed · 30 students
- 100%7
- 100%6
- 100%6
- 100%11
- Pass a later round: 100% (30 students), compared with 96% (96 students) on the ordinary exam
- Get 4 or 5: 71% (126 students)
Show small sittings (4)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 0%1
- 100%4
- 100%1
- 100%4
About the course
Aim
After completing the course, the student shall be able to:
- Classify typical user tasks for visualizations in context of the domain situation.
- Define and explain the visualization techniques (regarding interaction and visual representation) and example tools discussed in the course.
- Describe validation and evaluation methods for information visualization tools and approaches.
- Represent data by expressive and effective visualizations using stateofthe art methods, software, and tools.
- Critically reflect on visualization and interaction approaches in the light of current theories and research.
- Make wellgrounded design choices in the context of various tasks and data constraints.
Content
Information visualization centers on abstract information that does not have a physical or geometric correspondence to the real world. Examples of such abstract data are symbolic, tabular, networked, hierarchical, or textual information sources. The course provides an overview of the most common information visualization techniques and their application. The following topics are covered:
- Definition of the field of information visualization and relationships to related fields such as human-computer interaction or scientific visualization
- Data and visualization foundations and processing
- Data and task abstractions
- Interaction concepts and techniques (e.g., dynamic queries, zoom and pan, or focus and context)
- Visualization techniques for 1D, 2D, 3D, and multidimensional data
- Visualization techniques and drawing conventions for trees/hierarchies, general network data (graphs), and multivariate/dynamic networks.
- Validating and evaluating visualizations
- Overview of current systems and toolkits for information visualization
- Examiner
- Andreas Kerren
- Scheduled hours
- 51 h
- Main field of study
- Datateknik, Datavetenskap, Medieteknik