Volume 36 (2017)

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Adaptable Radial Axes Plots for Improved Multivariate Data Visualization
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Rubio-Sánchez, Manuel; Sanchez, Alberto; Lehmann, Dirk J.; Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke
Radial axes plots are multivariate visualization techniques that extend scatterplots in order to represent high-dimensional data as points on an observable display. Well-known methods include star coordinates or principal component biplots, which represent data attributes as vectors that de ne axes, and produce linear dimensionality reduction mappings. In this paper we propose a hybrid approach that bridges the gap between star coordinates and principal component biplots, which we denominate adaptable radial axes plots . It is based on solving convex optimization problems where users can: (a) update the axis vectors interactively, as in star coordinates, while producing mappings that enable to estimate attribute values optimally through labeled axes, similarly to principal component biplots; (b) use different norms in order to explore additional nonlinear mappings of the data; and (c) include weights and constraints in the optimization problems for sorting the data along one axis. The result is a exible technique that complements, extends, and enhances current radial methods for data analysis.