Proj 3 - Student Defined Visualization Project
Posted: Fri Dec 23, 2022 8:05 am
Proj 3 - Student Defined Visualization Project
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DETAILS
The final project integrates all things learned through the course, such as asking an interesting MysQL question, working with large data, and visualizing the data through Processing. The big difference is that each student selects their dat and visualization design. Data must be multi-dimensional and visualization has to be in 3D.
Your first task is to identify and select your data. Some of you may be working with datasets in your studies. This is the opportunity to try an alternative visualization of the data. Key current research topics of interests include environmental data, political data, news language analysis, bio diversity, etc. One of the challenges for datavis is that it takes time to learn what the data can do, so continuation with working with the Seattle library data is also an option.
Project criteria evaluation: Significant effort in innovative approaches in data content, data sampling and analysis, are a key to a successful project. Data can also be correlated between multiple sources. Visualization software environment to be used is Processing but data pre-processing can be done in other softwares like Python or R. In fact the Processing interface does have a Python and R so these are also possibilities.
The data should be relevant and granular, meaning that there should be a significant density of data to be visualized in 3D space. Each data’s x,y,z position should be directly defined by the data’s values. Preference is for the data to determine the visual form, rather than matching data to an existing form, for instance, a geographic map has a pre-determined visual/spatial organization.
The project should reveal an understanding of how to use spatial relationships, color coding, interaction methods, and all the features of visual language basics covered in the previous demos and projects.
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--------------
DETAILS
The final project integrates all things learned through the course, such as asking an interesting MysQL question, working with large data, and visualizing the data through Processing. The big difference is that each student selects their dat and visualization design. Data must be multi-dimensional and visualization has to be in 3D.
Your first task is to identify and select your data. Some of you may be working with datasets in your studies. This is the opportunity to try an alternative visualization of the data. Key current research topics of interests include environmental data, political data, news language analysis, bio diversity, etc. One of the challenges for datavis is that it takes time to learn what the data can do, so continuation with working with the Seattle library data is also an option.
Project criteria evaluation: Significant effort in innovative approaches in data content, data sampling and analysis, are a key to a successful project. Data can also be correlated between multiple sources. Visualization software environment to be used is Processing but data pre-processing can be done in other softwares like Python or R. In fact the Processing interface does have a Python and R so these are also possibilities.
The data should be relevant and granular, meaning that there should be a significant density of data to be visualized in 3D space. Each data’s x,y,z position should be directly defined by the data’s values. Preference is for the data to determine the visual form, rather than matching data to an existing form, for instance, a geographic map has a pre-determined visual/spatial organization.
The project should reveal an understanding of how to use spatial relationships, color coding, interaction methods, and all the features of visual language basics covered in the previous demos and projects.
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