Course syllabus
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
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19/1 |
10.15-12.00 Lecture: Course Intro and Information Visualisation Overview 13:15-16.00 Lecture and Exercise: Properties of Human Perception |
22/1 |
10:15-12.00 Lecture: Information Visualization Techniques & Design Process
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26/1 |
10.15-12.00 Lecture: Information Visualization in Games 13:15-16.00 Exercise: Information Visualization in Games |
29/1 |
10:15-12.00 Lecture: Interactivity in Information Visualization |
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2/2 |
Charm event - no course activities |
5/2 |
9.15-12.00 Guest Lecture: Data Storytelling |
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9/2 |
09.15-12.00 Lecture: Dark Information Visualization 13:15-16.00 Exercise: Dark Information Visualization |
12/2 |
09.15-12.00 Supervision |
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16/2 |
09.15-12.00 Supervision Deadline Home Exam, pt. I
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19/2 |
10.15-12.00 Supervision 13.15 - 16.00 Supervision |
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23/2 |
09.15-12.00 Guest Lecture: City Information Visualization password is: 13.15-17.00 Exercise: City Information Visualization |
26/2 |
09.15-12:00 Guest lecture: Maria Redström |
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2/3 |
09.15-12.00 Supervision 13.15 -16.00 Supervision |
5/3 |
09:30 -12.00 Deadline Design project
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9/3 |
09.15-12.00 Supervision |
12/3 |
09.00-12.00 Supervision |
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16/3 |
09.15-12.00 Supervision |
19/3 |
09.15-12.00 SupervisionDeadline 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 summary:
| Date | Details | Due |
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