TEK9600 – Visualization of Scientific Data
Changes in the course due to coronavirus
Autumn 2020 we plan for teaching and examinations to be conducted as described in the course description and on semester pages. However, changes may occur due to the corona situation. You will receive notifications about any changes at the semester page and/or in Canvas.
Spring 2020: Teaching and examinations was digitilized. See changes and common guidelines for exams at the MN faculty spring 2020.
The course provides an introduction to basic concepts of visualization and computer graphics. Key objectives of the course are to introduce useful tools and concepts for scientific visualization. It not only focuses on how and what we visualize, but also why. The course also deals with advanced data visualization and rendering techniques. The data used as examples in the course are taken from, among other things, numerical flow physics and medicine.
After completing this course, you will have:
- Experience in using basic and advanced techniques to visualize scientific data.
- Knowledge on why we need visualization.
- Knowledge of what we visualize and how.
- Basic knowledge in computer graphics.
- Knowledge of techniques for visualizing scalar, vector and tensor data.
- Knowledge of basic and advanced rendering techniques, with special emphasis on volume rendering, as well as knowledge of concepts such as photo-realistic and non-photo-realistic rendering.
- Knowledge of advanced flow visualization techniques such as Line Integral Convolution, Illuminated field lines and Anisotropic Diffusion.
- Knowledge of motion, "kinematics", and animation techniques for time-varying data.
- A good basis for scientific visualization in further studies in physical and mathematical subjects, in computer science and in medicine.
Admission to the course
PhD candidates from the University of Oslo should apply for classes and register for examinations through Studentweb.
If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included. Some national researchers’ schools may have specific rules for ranking applicants for courses with limited intake capacity.
PhD candidates who have been admitted to another higher education institution must apply for a position as a visiting studentwithin a given deadline.
Recommended previous knowledge
Some knowledge in mathematics and programming will be an advantage.
- 10 credits overlap with TEK5600 – Visualization of Scientific Data.
- 10 credits overlap with UNIK4660 – Visualization of scientific data (continued).
- 10 credits overlap with UNIK9660 – Visualization of scientific data (continued).
- 9 credits overlap with UNIKI-VAVD.
3 hour lectures per week throughout the semester. There will be mandatory assignments which must be approved in order to the exam.
Oral exam in the ends of the semester which counts 100% of the final grade. In case of many students, the exam may be written instead.
There will be mandatory assignments which must be approved in ordner to take the exam.
Ph.D-candidates will, in contrast to the master students on the cloned version of this TEK5600 – Visualization of Scientific Data, have an extended curriculum on streaming visualization.
Examination support material
No examination support material is allowed.
Language of examination
Subjects taught in English will only offer the exam paper in English. You may write your examination paper in Norwegian, Swedish, Danish or English.
Grades are awarded on a pass/fail scale. Read more about the grading system.
Resit an examination
Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester. Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.