Information Visualisation

706.057 Information Visualisation 3VU SS 2014

Lecturer: Ao.Univ.-Prof. Dr. Keith Andrews
Course Web Site: http://courses.iicm.tugraz.at/ivis/
My Web Site: http://www.iicm.tugraz.at/keith
Email: kandrews@iicm.edu
Office Hour: Mon. 11:00-12:00 during normal term
Room D.2.16, ID01054, IICM, Inffeldg. 16c, 1st floor.
Lectures:

Weds. 14:15 - 16:45
Seminar Room IICM, IDEG134, D.1.10, Inffeldgasse 16c, ground floor

Schedule: The course schedule in more detail.

Information about the oral exam.
Description:
1. Introduction
2. History of Information Visualisation
3. Visual Perception
4. Visualising Linear Structures
5. Visualising Hierarchies
6. Visualising Networks and Graphs
7. Visualising Multidimensional Metadata
8. Visualising Text and Object Collections
9. Visualising Query Spaces
10. Tools and Toolkits
11. Open Data Vis and Data Journalism
Aims and Objectives of Course: First we will look at current work and results in the area of information visualisation. Then students will resarch and present one particular aspect of information visualisation. Finally, students will design their own visualisation for a particular kind of information or application.
Teaching method: A mixture of lecture, seminar, and practical, with group discussion.
Lecture Notes: http://courses.iicm.tugraz.at/ivis/ivis.pdf [104 pages PDF]

The lecture notes will be updated as the course progresses.

[If you teach InfoVis and would like a zip file of the corresponding lecture slides (the same material but in HTML, PNG, and JPEG), please contact me by email.]

Course Books:

If you would like to buy one or two books for the course, I recommend the following:

Spence, Information Visualization, 2nd Edition Ward et al, Interactive Data Visualization Ware, Information Visualization: Perception for Design, 3rd Edition Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics

Note: Amazon credit me a small referal amount, should you purchase a book after following these links.

Surveys:

There are instructions for writing a survey paper.

You can also look at the survey papers from previous semesters of InfoVis.

Note that these are provided as they were handed in, warts and all. No rounds of reviewing or correction have taken place.

Course Newsgroup: tu-graz.lv.ivis
Registration:

In TUGrazOnline.

This is an advanced course at postgrad (Master's) level. The number of students is limited to 20 to encourage participation and discussion. Places often fill up very fast.

Priority will be given to PhD and Master's students in one of the computer science degree programmes (Main Group). Students in other degree programmes will be allocated places at the first lecture in chronological order of registration as far as places are still available (Reserve Group).

After the unregistration deadline, if you wish to unregister from the course, please contact me by email. Depending on how far the course has already progressed, I will either unregister you without penalty or (more likely) grade your work up to that point.

Examination Method: The grade will be determined by your group presentation of a research topic (20%), the group development of an infovis prototype (40%), and an individual oral exam (40%).
Language Policy:

This course is taught in English and there may be some participants who do not speak German, so please give your presentations and write your reports in English. This course is a good chance to practice using English with (almost) nothing to lose. I will not be grading your English, but the content of your work.

For the oral exam, you can choose whether the exam is in English or German.

Plagiarism Policy:

Do not cheat. Copying from the web or copying the work of others and then submitting it as your own is known as plagiarism. Plagiarism is strictly forbidden and will be punished where discovered. The university has a code of conduct and set of guidelines regarding scientific integrity and ethics.

By taking this course, you agree to have your work submitted to plagiarism detection services. We also cross-check work against other work submitted in the same and previous years.