|Lecturer:||Ao.Univ.-Prof. Dr. Keith Andrews|
|Course Web Site:||
|My Web Site:||
Mon. 11:00-12:00 during normal term
Room D.2.16, ID01054, IICM, Inffeldg. 16c, 1st floor.
Weds. 14:15 - 16:45.
The course schedule in more detail.
Information about the oral exam.
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 work.|
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.]
If you would like to buy one or two books for the course, I recommend the following:
Note: Amazon credit me a small referal amount, should you purchase a book after following these links.
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.
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%).|
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.
|Breaches of Academic Integrity:||
Do not plagiarise. Copying the work of others (from the web or elsewhere) or copying from another group and then submitting the work as (part of) your own work is known as plagiarism and is a serious breach of academic integrity. By taking this course, you agree to have your work submitted to plagiarism detection services. Your work may also be cross-checked against other work submitted in the same and previous years.
Do not fake. Faking data (for example, inventing the results of a survey or poll) is a serious breach of academic integrity.
The university has a code of conduct and set of guidelines regarding scientific integrity and ethics. Breaches of academic integrity are very serious and will be punished appropriately where discovered.