TEK9600 – Visualization of Scientific Data
Course description
Schedule, syllabus and examination date
Course content
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.
Learning outcome
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 student within a given deadline.
Recommended previous knowledge
Some knowledge in mathematics and programming will be an advantage.?
Overlapping courses
- 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.
Teaching
3 hours of lectures per week throughout the semester.
There will be mandatory assignments which must be approved before you sit the exam.?
PhD candidates will, in contrast to the master's students on the cloned version of this course TEK5600 – Visualization of Scientific Data, have an extended curriculum on streaming visualization.
The course lectures are given at the Department of Technology Systems in Kjeller Research Park. See the schedule for the student bus from Campus Blindern.
Examination
- A final oral exam counts 100% towards the final grade.
- In case of many students, the exam may be written instead.?
- The course has mandatory assignments which must be approved before you sit the final exam.?
It will also be counted as 1 of the 3 attempts to sit the exam for this course, if you sit the exam for one of the following courses:
- UNIK4660 – Visualization of scientific data (continued)
- UNIK9660 – Visualization of scientific data (continued)
- TEK5600 – Visualization of Scientific Data
Examination support material
No examination support material is allowed.
Language of examination
Courses taught in English will only offer the exam paper in English. You may write your examination paper in Norwegian, Swedish, Danish or English.
Grading scale
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.
More about examinations at UiO
- Use of sources and citations
- Special exam arrangements due to individual needs
- Withdrawal from an exam
- Illness at exams / postponed exams
- Explanation of grades and appeals
- Resitting an exam
- Cheating/attempted cheating
You will find further guides and resources at the web page on examinations at UiO.