Information Visualisation

Level: Master
Semester: 2nd Semester (February - June)
Language: English
Teacher: Beat Signer
Assistant(s): Yoshi Malaise
Course Description

In this course students learn about the representation (abstraction) and presentation of data in terms of different visualisation techniques supporting the exploratory analysis for scientific discovery as well as the design of tools for the presentation of large datasets. The theory further covers specific elements of human perception and colour theory and we discuss different design principles and interaction techniques for human-in-the-loop data exploration underlined by various case studies. The theory is applied and further deepened in a group assignment where interactive visualisations are designed and implemented for different rich datasets.

Lectures: Thursday, 10:00-12:00, D.2.14
Exercises: Group 1 - Thursday, 13:00-15:00, E.1.05, Group 2 - Thursday, 15:00-17:00, E.1.05

Please note that the order of the lecture and exercise slots as well as the location of the exercise slots might change for some weeks.


Lecture Schedule

Lecture 1:  Introduction


Lecture 2:  Human Perception and Colour Theory


Lecture 3:  Data Representation


Lecture 4:  Analysis and Validation


Lecture 5:  Data Presentation


Lecture 6:  Data Processing and Visualisation Toolkits


Lecture 7:  Design Guidelines and Principles


Lecture 8:  Visualisation Techniques


Lecture 9:  View Manipulation and Reduction


Lecture 10:  Interaction


Lecture 11:  Dashboards


Lecture 12:  Case Studies and Course Review


Lecture 13: Final Project Presentations