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Course module: JM0250-M-6
JM0250-M-6
Data Visualization
Course info
Course moduleJM0250-M-6
Credits (ECTS)6
CategoryMA (Master)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Economics and Management; TiSEM: Management; TiSEM: Management;
Is part of
M Data Science and Entrepreneurship (joint degree)
Contact personprof.dr.ir. J.J. van Wijk
Lecturer(s)-
Starting block
C1
Course mode
Full-time
RemarksThis information is not up to date. Check the Course Catalog 2018 or select the course via “Register”.
Registration opennot known yet
Aims
After the course, students should
have nowledge and understanding of basics of:
- (visual) design
- perception
- visual mapping of data
- interaction
be able to apply their knowledge and understanding to
- analyse visualization problems: who and what?
- design visualizations: how?
- implement visualizations.

 
Specifics
The courses from the Data Science and Entrepreneurship program require specific prior knowledge. It is only possible to participate in this course if approved by the admission committee and if you are enrolled for the program.
Please note that this course will be taught in Mariënburg, ‘s-Hertogenbosch (JADS).
Content
The aim of the course is to train students in the design and analysis of data visualization, with a strong focus on abstract data. Topics discussed are:
- Visualization in general: pipeline model, purposes and categories of visualization;
- Design: nested process model, design thinking, graphics design;
- Perception and cognition: understanding strengths and limitations of the human brain, and how to exploit these;
- Interaction: enabling exploration of data;
- Visualization methods: visualization of multivariate data, hierarchical data, network data, geographic data, text, story telling;
- Visualization technology: frameworks and tools for producing visualizations.
The focus of thee course is not on technology, this is not a D3-course. Technology changes rapidly, an understanding of principles how to communicate and explore data and how to reflect on this is more important.
The lecture hours are used for formal lectures, workshops, discussion of homework exercises, and presentations of students. Students do 4-5 individual assignments, and one team project.

 
Recommended Reading
  1. Tamara Munzner, Visualization Analysis and Desicn, AK Peters, 2014, ISBN 9781466508910. Thorough and extensive treatment of data visualization
  2. Stephen Few, Now you see it: Simple Visualization Techniques for Quantitative Analysis, Analytics Press, 2009. Practical introduction to data visualization
  3. Colin Ware, Visual thinking for design, Morgan Kaufmann, 2008, ISBN 9780123708960. Excellent description of human visual perception for design purposes
 
Required Prerequisites
Basic computer skills
Required materials
-
Recommended materials
-
Tests
Other_1

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Kies de Nederlandse taal