Sample Projects
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Visualization in practice is often done without strategy. 3D graphics and visualization tools are used until the result seems suitable. It is very important to have students of a visualization course work with real data to generate expressive and effective visualizations. They need to learn to use mapping strategies for visualization (see Theme 4) to arrive at representations that can be interpreted or explored quickly and accuratly. We have gathered three data sets. For each of the data sets the students should discuss:
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Problem domain (E.g. What is the background of the problem? Will experts of certain disciplines need to interpret resulting pictures? Is the use of specific visual attributes, such as colors, or visual representations "common sense" for these users? )
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Data model (What do I know of the data - their origin, characteristics, default representations, ...?)
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Visualization goals/tasks (What are the questions users will try to answer from the representations)?
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User characteristics (What do I know of the user - desires, abilities, disabilities... ?)
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Possible representations (What representations are expressive for this data model? Out of these, which are effective for the specific user and task?)
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Necessary interactions (Is interaction necessary, what kind, can it be done with available hardware/software?)
- Possible tools to use to generate representations (what libraries or tools will be able to help generate useful visualizations, what kind of visual context will be necessary)?
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How will the students know their solution is a useful (visual) representation?
before they start with programming.
It will be gratifying to see how students improve their pictures while their knowledge on the visualization process improves. It might be worth having them redo projects again at the end of their course to see what they missed the first time. Having each student (or group of students) present their project in front of the class, everyone will learn from other mistakes and ideas.
Have fun!