What are the main disadvantages of 3D visualizations in general?


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A common disadvantage of 3D visualizations is, for instance, occlusion. What are the main drawbacks and disadvantages of 3D visualizations and what are common approaches to resolve or prevent them?


We may first separate datasets featuring 3D spatial information (e.g., 3D geometric models, 3D volume data) from those datasets featuring 3 or more variables but not “naturally” 3D spatial information. In the former cases, 3D visualization usually allows users to relate what is displayed to what they know more easily. For example, when a doctor sees the visualization of a heart (in a 3D-to-2D projection), he/she can reconstruct the 3D shape/structure (including the occluded parts) without much effort. For an unfamiliar object (e.g., an engine block), the doctor may have to use more interactions (e.g., rotating and zooming) to figure out the shape/structure.

For the latter cases, when the 3D spatialization appears to be unnatural for the datasets, users have to use more cognitive load to construct a representative mental impression of the data. So the 3D spatialization may stimulate undesired distortion during the reconstruction, e.g., due to humans’ natural intuition to interpret distances, sizes, and occlusions with perspective projections in mind. However, in some cases, stimulating such intuition may be desirable (e.g., for memorization or visual metaphors in disseminative visualization). Occlusions are themselves not necessarily always a problem. Some occlusions (e.g., lines in parallel coordinates) are less problematic than others, which fundamentally depend on humans’ ability to reconstruct the whole shape from a partial, translucent, or deformed view, and the cost of using interaction to reveal the occluded objects. Dealing with occlusions in visualization is closely related to visual multiplexing (Chen et al. CGF, 2014).


Thank you for your quick response!
Does that mean it can be assumed that 3D increases in general the probablity of introduced error due to increased difficulty of the observer to reconstruct/transform the given information. At least with regard to the latter case (abstract, no “natural” relation to 3D).
For instance bar charts or scatter plots might be interpreted wrong, as, for instance, the common baseline “disappears” or moves due to the angle of perception and the spatial ordering of bars/points.

Just to collect some possible drawbacks of 3D visualizations that should be considered when designing ones:

  • distortion of information and wrong interpretation (common baseline, comparison of entities, distance - e.g., futher appart entities appear smaller…)
  • interaction might be required
  • occlusion might be a problem


This depends on the tasks of visualization. For example, let us compare a data table display, a 3D scatterplot, two 2D scatterplots, and a parallel coordinates plot for a set of trivariate data points. In terms of seeing a triviate value correctly, the table will likely be the best! In terms of identifying clusters and outliers, the order from more effectively to less might be a 3D scatterplot (with interaction), parallel coordinates, two 2D scatterplots, a 3D scatterplot (without interaction), and a data table. The 2D part of the comparison can be found in Kanjanabose et al. CGF 2015. Of course, ideally one would like to reconstruct the values of each data point correctly. However, in practice, the task determines mainly the desired benefit and the visual representation and user knowledge affects mainly the cost. The best visual representation reflects the best cost-benefit ratio [Chen & Golan, TVCG, 2016].

In terms of 3D bar charts, it is actually reasonably natural to most users who can get this visual metaphor easily. If the bars CAN be ordered according to the heights with higher bars at the back, the cost of reconstruction is relatively lower. However, if the reordering along the x-y axes may incur extra cognitive load, one has to compare such cost against the cost of interaction. In this case, different visualization tasks may have different restrictions or cost-benefit ratio about the axis re-ordering.


Thank you for your explanation! I guess a broad generalization of disadvantages of 3D visualizations is harder than I thought. … Which is also a good thing as it says that 3D is also reasonable in various cases.