Descripción
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Most visualization techniques have traditionally used 2D, instead of 3D representations to visualize multidimensional and multivariate data. In this paper, a way to demonstrate the underlying superiority of 3D, with respect to 2D representations, is proposed. Speci?cally, it is based on the inevitable quality degradation produced when reducing the data dimensionality. The problem is tackled from two dierent approaches: a visual and an analytical approach. Firstly, a set of statistical tests (point classi?cation, distance perception and outlier identi?cation) using the 2D and 3D visualization are carried out on a group of 40 users. The results indicate that there is an improvement in the accuracy and e?ciency introduced by the inclusion of a third dimension, however these results do not allow to obtain de?nitive conclusions on the superiority of 3D. Therefore, in order to draw further conclusions, a deeper study based on an analytical approach is proposed. The aim is to quantify the real loss of quality produced when the data is visualized in 2D and 3D spaces, in relation to the original data dimensionality, to analyze the dierence between them. To achieve this, a recently proposed methodology [1] is used. The results obtained by the analytical approach reported that the loss of quality, reaches signi?cantly high values only when switching from 3D to 2D. The considerable quality degradation suered in the 2D visualization strongly suggests the suitability of the third dimension to visualize data. | |
Internacional
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JCR del ISI
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Si |
Título de la revista
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Information Visualization |
ISSN
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1473-8716 |
Factor de impacto JCR
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1 |
Información de impacto
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Volumen
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DOI
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Número de revista
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