Course-PM

CIU187 / DIT109 Information visualization VT22 (7,5hp)

Revised Jan 16th , 2024

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 endeavour 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 at 10:15 Tuesday, January 16^th . The courses and exercises will take place on campus, the supervision sessions will be conducted via Zoom (the links will be provided in the schedule below).

Contact details

Teachers

Jasmina Maric (jasmina@chalmers.se)

Staffan Björk (staffan.bjork@cse.gu.se)

Georgios Diapoulis (georgios.diapoulis@chalmers.se)

TA

Yue Lou (yuelo@student.chalmers.se)

Course communication

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

 

Course literature

Tamara Munzner. Visualization Analysis and Design. A K Peters Visualization Series, CRC Press, 2014. 

 

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 mainly be based on the Home Exam and the Group project grade. See below for more details.

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

Video lectures. Links to a selection of video lectures that cover specific chapters of the course book are provided in one of the Modules. 

Exercises are independent group work, completing an assignment. 

 

Schedule

Note: TimeEdit does show the times and dates for activities but does not show the location properly, and time and dates may change here; use TimeEdit as the last backup. 

 

Changes made since the last occasion

The most prominent changes from the previous course are:

• Change of the course team
• Change of exercise 4

 

Examination form

The course is examined using three modules, namely:

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

 

Grade Scale

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 exercises, the group project and the home exam(s). The grade for Home Exam is the average of the two Home Exam parts. The course grade is based on the Group Project grade (33% of the grade) and the Home Exam grade (67% of the grade) and 

To pass the course you must do a minimum of 3 exercises out of 4.

 

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

 

Student Representatives

 

 

Course Plans

Course description at Chalmers

Course description at the University of Gothenburg