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Scientific Visualization, 6 credits
Vetenskaplig visualisering, 6 hp
TNM067
Main field of study
Information Technology Computer Science and Engineering Media Technology and EngineeringCourse level
Second cycleCourse type
Programme courseExaminer
Ingrid HotzDirector of studies or equivalent
Camilla ForsellEducation components
Preliminary scheduled hours: 48 hRecommended self-study hours: 112 h
Available for exchange students
YesECV = Elective / Compulsory / Voluntary
Main field of study
Information Technology, Computer Science and Engineering, Media Technology and EngineeringCourse level
Second cycleAdvancement level
A1XCourse offered for
- Media Technology and Engineering, M Sc in Engineering
- Computer Science and Engineering, M Sc in Engineering
- Applied Physics and Electrical Engineering, M Sc in Engineering
- Biomedical Engineering, Master's programme
- Mathematics, Master's programme
- Information Technology, M Sc in Engineering
- Applied Physics and Electrical Engineering - International, M Sc in Engineering
- Computer Science and Software Engineering, M Sc in Engineering
- Computer Science, Master's programme
Specific information
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Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
Computer Graphics, Physical modeling
Intended learning outcomes
The goal for this course is to provide the student with deep insights into methods for visualization of scientific data from experiments and simulations. The applicability of the various methods is shown through practical programming exercises. Upon completion of the course the student should be able to:
- For a given data set choose an appropriate visualization method.
- Design and implement a visualization tool using the chosen. method and available software toolkits.
- Read and present the content in scientific papers in the field.
Course content
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Introduction to visualization: visualization as a research field, applications, tasks
- Visualization pipeline
- Data representation and interpolation:
- Basic data types: Scalar, vector and tensor data
- Structured and unstructured data
- Basic visualization algorithms
- for scalar fields, e.g. color mapping, contour lines and surfaces
- for vector fields, e.g. flow lines and surfaces and time animation of these
- for tensor fields, e.g. glyphs, tensor lines
- Overview of techniques for volume rendering
- Introduction to concepts for more advanced visualizations data analysis
- data exploration
- feature extraction
- topological methods
- Examples of some application specific visualization techniques
The knowledge gained is applicable in several existing and emerging applications in industry and the public sector, but can also form the foundation of research and development in scientific visualization both within academia and specialized companies.
Teaching and working methods
The course is composed of lectures and laboratory assignments. Scientific papers will also be included as self-study material.
Examination
| MUN1 | Oral examination | 3 credits | U, 3, 4, 5 |
| LAB1 | Laboratory work | 3 credits | U, G |
Grades
Four-grade scale, LiU, U, 3, 4, 5Department
Institutionen för teknik och naturvetenskapDirector of Studies or equivalent
Camilla ForsellExaminer
Ingrid HotzCourse website and other links
http://scivis.itn.liu.se/teaching/courses/scientific-visualization/Education components
Preliminary scheduled hours: 48 hRecommended self-study hours: 112 h
| Code | Name | Scope | Grading scale |
|---|---|---|---|
| MUN1 | Oral examination | 3 credits | U, 3, 4, 5 |
| LAB1 | Laboratory work | 3 credits | U, G |
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.
Course literature is preliminary.
There is no course literature available for this course in studieinfo.
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
|---|---|---|---|---|---|---|
| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
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X
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X
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| 1.2 Fundamental engineering knowledge (G1X level) |
X
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X
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X
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
X
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X
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X
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
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X
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| 2.2 Experimentation, investigation, and knowledge discovery |
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| 2.3 System thinking |
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X
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| 2.4 Attitudes, thought, and learning |
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| 2.5 Ethics, equity, and other responsibilities |
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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X
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| 3.2 Communications |
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X
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| 3.3 Communication in foreign languages |
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
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X
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| 4.4 Designing |
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X
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| 4.5 Implementing |
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| 4.6 Operating |
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
X
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| 5.4 Execution of research or development projects |
X
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| 5.5 Presentation and evaluation of research or development projects |
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