Home
Student Pages
Postgraduate course

Seminar in Visualization

ECTS Credits

10 ECTS

Level of Study

Master/ PhD

Full-time/Part-time

Full-time

Teaching semester

Autumn

Objectives and Content

Objectives:
The main objective of course INF358 is twofold: On the one hand, students are introduced to a variety of visualization solutions (tools) and exercise them on selected datasets, while, on the other hand, the students are also introduced to the basic methods of scientific work, ranging from literature research to presenting own research. After the successful completion of course INF358, students know about common solutions/tools in visualization and how to use them; they have also learned the principal practices of scientific work and acquired first experiences with them.

Content:
Course INF358 addresses a variety of visualization cases, including tabular data visualization, time-dependent data visualization, graph visualization, and scientific data visualization. In terms of the principles of scientific work, course INF358 addresses literature research and literature review, doing scientific work based on related work, as well as writing and presenting own (scientific) work.

Learning Outcomes

After the successful completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge
The student

  • knows about tools and methods to visualize tabular data
  • knows about tools and methods to visualize time-dependent data
  • knows about tools and methods to visualize graph data
  • knows about tools and methods to visualize scientific data (gridded data)
  • knows about how to search and find related literature
  • knows about how to discuss related workknows about how to do own (scientific) work, based on related work
  • knows about how to write (scientifically) about own (research) work
  • knows about how to present (scientifically) own (research) work

Skills
The student

  • is capable of applying an appropriate visualization solution (tool) to tabular data
  • is capable of applying an appropriate visualization solution (tool) to time-dependent data
  • is capable of applying an appropriate visualization solution (tool) to network data
  • is capable of applying an appropriate visualization solution (tool) to scientific data (gridded data)
  • is capable of searching and finding scientific literature that is related to a given research problem
  • is capable of developing an own solution based on related research work
  • is capable of scientifically writing a publication of own (research) work
  • is capable of scientifically presenting own (research) work

General competence
The student

  • can evaluate the appropriateness of a given visualization solution / tool for a given (research) problem
  • appreciates the usual practices of scientific work, including ethical considerations such as being truthful to related work

Credit Reduction due to Course Overlap

VISUAL: 10 ECTS

Access to the Course

Access to the course requires admission to a master's programme at The Faculty of Mathematics and Natural Sciences

Teaching and learning methods

Teaching is done in the form of lectures, group meetings, and exercises.

  • Lectures (about 12 double-units throughout the semester),
  • group meetings (about 8 double-units throughout the semester),
  • exercises (about 10 assignments with a deadline every other week).

Compulsory Assignments and Attendance

The students must achieve at least 50% of all possible points at the exercises.

Forms of Assessment

The form of assessment is:

  • exercises (100% of the overall grade)

Examination Support Material

None

Grading Scale

The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.

Assessment Semester

Examination both spring semester and autumn semester. In semesters without teaching the examination will be arranged at the beginning of the semester.

Reading List

The reading list will be available within June 1st for the autumn semester and December 1st for the spring semester.

Course Evaluation

The course will be evaluated by the students in accordance with the quality assurance system at UiB and the department.

Programme Committee

The Programme Committee is responsible for the content, structure and quality of the study programme and courses.

Course Coordinator

Course coordinator and administrative contact person can be found on Mitt UiB, or contact Student adviser

Course Administrator

The Faculty of Mathematics and Natural Sciences represented by the Department of Informatics is the course administrator for the course and study programme.

Contact

Contact Information

Student adviser:

Student adviser

T: 55 58 42 00

Exam information