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Visual Analytics

Homework #4

Meili Vanegas

Juan Sebastian Martinez

The visualization presented here is an alternative to the AADV 3D visualization presented in, which displays all the determinant metrics used to calculate the Environmental Performance Index (EPI) for all countries.

AADV's Visualization Analysis

The 3D visualization uses areas as marks and both position and size as channels to communicate the different factors used to calculate the EPI score. The main problem with this visualization is that the 3D surfaces overlap, making it difficult to compare scores between different metrics.

In the visualization, factors represent categorical data, and the score for each factor represents numerical data. We can say that the task that the visualization wants to aid is to present the scores of all factors for a given country. With this in mind, the 3D polygonal representation used violates the principle of effectiveness, as it uses areas and depth for the numerical scores presented, which happens to be a low-effective channel for this type of data and makes it difficult to present the scores and to accomplish the final task.

On the other hand, the polygonal 3D representation resembles the data distribution in a pie chart, which tries to show the weight of every factor as the area occupied in the polygon. This gives a good perception of expressiveness, although other representation could be better (thickness of bars in a bar chart for example), as we know that angles are not very effective to communicate information to the human eyes.

forked from mvanegas10's block: Nigeria