Information visualization

Note: the course pages are being updated so changes can occur until the start of the course.

Course-PM

CIU187 / TIA109 Information visualization VT20 (7,5hp)

Revised January 18th, 2021

Department of Computer Science and Engineering

Course purpose

In this course we will study the science, craft and art of visualizing information. A basic premise in this endeavor is that visualization is an extension of our minds into the world and a powerful cognitive tool to both perceive and communicate information. It extends our senses and provides new ways to express our ideas, facilitating both exploration of the world (and data representing the world) and sharing of information and understanding. As such, an understanding of human perception as well as the technological means for creating visualizations provides the basis for knowledgeable work with information visualization.

Course start

The course starts 10:15 Tuesday January 19th, in Zoom (see Schedule below for link).

Contact details

Teachers

Jasmina Maric (jasmina@chalmers.se)

Staffan Björk (staffan.bjork@gu.se)

Teacher Assistants

Premthip Yaowapatsiri

Xinshu Li

Course communication

Course communication will be through this Canvas room, including announcements. Students that wish to contact teachers can do so through personal messages in Canvas or through email. Zoom will be used for all teaching, including supervision.

Course literature

Spence, R. (2014). Information Visualisation. An Introduction.

Course design

The theory introduced in lectures will be combined with group exercises to introduce tools and technologies. Practical experience can be gained through the group project. A two-part home exam frames the course, the first part testing understanding of theoretical concepts and analytical abilities and the second part testing abilities to design and reflect on information visualizations. The grade will depend on the project in combination with a home exam. See below for more details.

Lectures . Slides will be provided after lectures but they will be designed to be presented live and provide material for discussion and explanations at lectures. They will not be designed to be read independently afterwards.

Exercises are independent group work, completing an assignment.

Schedule

 

TUESDAYS

FRIDAYS

 

19/1

10.15-12.00 Lecture: Course Intro and Information Visualisation Overview
with Staffan Björk

13:15-16.00 Lecture and Exercise: Properties of Human Perception
with Jasmina Maric

22/1

10:15-12.00 Lecture: Information Visualization Techniques & Design Process
with Jasmina Maric

 

26/1

10.15-12.00 Lecture: Information Visualization in Games
with Staffan Björk

13:15-16.00 Exercise: Information Visualization in Games
with Staffan Björk

29/1

10:15-12.00 Lecture: Interactivity in Information Visualization
with Jasmina Maric

2/2

Charm event - no course activities

5/2

9.15-12.00 Guest Lecture: Data Storytelling
with Yemao Man

9/2

09.15-12.00 Lecture: Dark Information Visualization
with Jasmina Maric

13:15-16.00 Exercise: Dark Information Visualization
with Jasmina Maric

12/2

09.15-12.00 Supervision

16/2

09.15-12.00 Supervision

Deadline Home Exam, pt. I

 

19/2

 10.15-12.00 Supervision

 13.15 - 16.00 Supervision

23/2

 09.15-12.00 Guest Lecture: City Information Visualization 
with Beata Wästberg

password is: InfoVis

 13.15-17.00 Exercise: City Information Visualization 
with Beata Wästberg

26/2

 09.15-12:00 Guest lecture: Maria Redström

 + Supervision

2/3

09.15-12.00 Supervision

13.15 -16.00 Supervision 

5/3

09:30 -12.00 Deadline Design project
Presentations design project
(groups 1-5) with Jasmina and Xinshu

Presentations design project 

(groups 6-10) with Staffan and Premthip

9/3

09.15-12.00 Supervision

12/3

09.00-12.00 Supervision

16/3

09.15-12.00 Supervision

19/3

09.15-12.00 Supervision

 Deadline Home Exam, pt. II

 

 

Lectures and exercises will be accessible through Zoom. (TimeEdit does show the times and dates for activities but do not show location properly, and time and dates may change here; use TimeEdit as the last backup). Note: they've had a technical issue with TimeEdit recently so all data is from early October (may be more relevant for other courses that you take, they are working on updating the data but this may take some time).

Changes made since the last occasion

The most prominent changes from 2019 are:

  • Removing requirements to code visualizations.
  • All activities digital this instance of the course due to Corona.

 

Examination form

The course is examined by means of three modules, namely:

  • Group Exercises 1.5 credit (fail/pass)
  • Group Project 2.0 credits (fail, 3, 4, 5 at Chalmers, fail/pass at GU)
  • Home Exam 4.0 credits (fail, 3, 4, 5)
    • Part One - Theory and Analysis
    • Part Two - Design and Reflection

 

Grade Scale - Chalmers

The grading scale comprises Fail (U), 3, 4 and 5. To receive a passing grade for the whole course, a student must have a passing mark on the exam, and both the assignments and the project. To get a 4 or a 5, a student must have a 4 or a 5 on the written exam and on the project.

 

Grade Scale - GU

The grading scale comprises: Pass with Distinction (VG), Pass (G) and Fail (U). To receive a passing grade for the whole course, a student must have a passing mark on the written exam, and both the exercise and the project. To pass with distinction, a student must have passed with distinction the written exam and have a passing mark on both the exercise and the project.

 

Learning objectives and syllabus

Learning outcomes (after completion of the course the student should be able to)

Knowledge and understanding 
* explain well-known information visualization techniques, including the pros and cons they have with respect to types of data and contexts
* describe how the cognitive and perceptive abilities of humans affect the possibilities of information visualization

Skills and abilities
* create concepts for information visualizations taking into consideration specific data sets, users, technologies, and use context
* develop visualizations from concepts to a functional prototype

Judgement and approach 
* evaluate different interactive visualization techniques to judge their effectiveness and suitability for both generic and specific use
* analyze and provide creative criticism on specific solutions to visualize information

 

Course Plans

Course description at Chalmers

Course description at the University of Gothenburg

Course summary:

Date Details Due