New insights into the suitability of the third dimension for visualizing multivariate/multidimensional data: A study based on loss of quality quantification. (January 2016)

• Record Type: Journal Article
• Authors: Gracia, Antonio; González, Santiago; Robles, Víctor; Menasalvas, Ernestina; von Landesberger, Tatiana
• Is Part Of: Information visualization. Volume 15:Number 1(2016:Jan.)
• Page Start: 3
• Page End: 30
• Publication Date: 2016-01
• Subjects: Two-dimensional -- three-dimensional -- manifold learning -- dimensionality reduction -- loss of quality -- quality assessment criteria -- multivariate data -- multidimensional data -- data visualization; Information visualization -- Periodicals; 006.605
• DOI: 10.1177/1473871614556393
• Languages: English
• ISSNs: 1473-8716

Abstract

Most visualization techniques have traditionally used two-dimensional, instead of three-dimensional representations to visualize multidimensional and multivariate data. In this article, a way to demonstrate the underlying superiority of three-dimensional, with respect to two-dimensional, representation is proposed. Specifically, it is based on the inevitable quality degradation produced when reducing the data dimensionality. The problem is tackled from two different approaches: a visual and an analytical approach. First, a set of statistical tests (point classification, distance perception, and outlier identification) using the two-dimensional and three-dimensional visualization are carried out on a group of 40 users. The results indicate that there is an improvement in the accuracy introduced by the inclusion of a third dimension; however, these results do not allow to obtain definitive conclusions on the superiority of three-dimensional representation. 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 are visualized in two-dimensional and three-dimensional spaces, in relation to the original data dimensionality, to analyze the difference between them. To achieve this, a recently proposed methodology is used. The results obtained by the analytical approach reported that the loss of quality reaches significantly high values only when switching from three-dimensional to two-dimensional representation. The considerable quality degradation suffered in the two-dimensional visualization strongly suggests the suitability of the third dimension to visualize data.