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Informatics 2019, 6(2), 16;

RadViz: Improvements on Radial-Based Visualizations++

Faculty of Science and Engineering, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands
Authors to whom correspondence should be addressed.
Received: 28 February 2019 / Revised: 4 April 2019 / Accepted: 4 April 2019 / Published: 9 April 2019
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RadViz is one of the few methods in Visual Analytics able to project high-dimensional data and explain formed structures in terms of data variables. However, RadViz methods have several limitations in terms of scalability in the number of variables, ambiguities created in the projection by the placement of variables along the circular design space, and ability to segregate similar instances into visual clusters. To address these limitations, we propose RadViz++, a set of techniques for interactive exploration of high-dimensional data using a RadViz-type metaphor. We demonstrate the added value of our method by comparing it with existing high-dimensional visualization methods, and also by analyzing a complex real-world dataset having over a hundred variables.
Keywords: radial-based visualizations; data analysis; edge bundling; visual scalability radial-based visualizations; data analysis; edge bundling; visual scalability
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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de Carvalho Pagliosa, L.; Telea, A.C. RadViz: Improvements on Radial-Based Visualizations++. Informatics 2019, 6, 16.

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