What Is 3D Data Visualization?

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  • Written By: Alex Newth
  • Edited By: Angela B.
  • Last Modified Date: 12 January 2020
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Three-dimensional (3D) data visualization refers to a computer program or other technology that enables users to see a visual representation — whether static or animated — of data on their computer. For most 3D data visualization programs, users are able to make a visualization of any local information, but web information may be limited. Unlike other visualization programs, 3D data visualization is intended to be in 3D, which makes this visually different from other types. Information in the visualization can either be static or dynamic.

The reason for 3D data visualization is to create a visual representation of information on a computer. This representation can be very simple, like a line graph representing the number of files on a computer, or it can be a complex web of nodes and information that interlink with other nodes. Visualizations can be static, meaning they do not move, or they can be animated with visualization nodes that can fly around the screen.

Most 3D data visualization programs enable users to create a representation of any information on a computer, especially local information stored on the hard drive. Web information may or may not be accessible, depending on the program. Since web information usually is dynamic instead of static, and because it can be harder to access, the visualization may be limited in what can be gathered.


In function, 3D data visualization is similar to other data visualization programs. The main difference between this and any other types is that all the visualizations are created in 3D, which gives the visualizations more depth. A beneficial byproduct of using 3D is that it typically is easier to make animations, and this gives visualization designers more to work with so they can make more visually striking representations.

When 3D data visualization is used, the representation can either be static or dynamic. Unlike being static or animated, which refers to the movement of the representation, this refers to the information itself and whether the visualization is self-updating. Static visualizations, in this regard, just show a snapshot of information and cannot change. Dynamic visualizations are self-updating; when a file or variable in the visualization changes on the hard drive or the web, the representation will immediately reflect this difference. Dynamic visualizations are more in-depth, so they often require more code to ensure the representation can update without shutting down, and more power typically is needed.


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