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