Document Type
Article
Department or Administrative Unit
Computer Science
Publication Date
2-3-2014
Abstract
Often multidimensional data are visualized by splitting n-D data to a set of low dimensional data. While it is useful it destroys integrity of n-D data, and leads to a shallow understanding complex n-D data. To mitigate this challenge a difficult perceptual task of assembling low-dimensional visualized pieces to the whole n-D vectors must be solved. Another way is a lossy dimension reduction by mapping n-D vectors to 2-D vectors (e.g., Principal Component Analysis). Such 2-D vectors carry only a part of information from n-D vectors, without a way to restore n-D vectors exactly from it. An alternative way for deeper understanding of n-D data is visual representations in 2-D that fully preserve n-D data. Methods of Parallel and Radial coordinates are such methods. Developing new methods that preserve dimensions is a long standing and challenging task that we address by proposing Paired Coordinates that is a new type of n-D data visual representation and by generalizing Parallel and Radial coordinates as a General Line coordinates. The important novelty of the concept of the Paired Coordinates is that it uses a single 2-D plot to represent n-D data as an oriented graph based on the idea of collocation of pairs of attributes. The advantage of the General Line Coordinates and Paired Coordinates is in providing a common framework that includes Parallel and Radial coordinates and generating a large number of new visual representations of multidimensional data without lossy dimension reduction.
Recommended Citation
Boris Kovalerchuk, "Visualization of multidimensional data with collocated paired coordinates and general line coordinates," Proc. SPIE 9017, Visualization and Data Analysis 2014, 90170I (3 February 2014); https://doi.org/10.1117/12.2042427
Journal
Proceedings of SPIE
Rights
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)
Comments
Copyright 2014 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.
This article was originally published in Proceedings of SPIE - Visualization and Data Analysis 2014. The full-text article from the publisher can be found here.