Smart Brushing for Parallel Coordinates

Roberts, Richard C.; Laramee, Robert S.; Smith, Gary A.; Brookes, Paul; D'Cruze, Tony

Abstract

The Parallel Coordinates plot is a popular tool for the visualization of high-dimensional data. One of the main challenges when using parallel coordinates is occlusion and overplotting resulting from large data sets. Brushing is a popular approach to address these challenges. Since its conception, limited improvements have been made to brushing both in the form of visual design and functional interaction. We present a set of novel, smart brushing techniques that enhance the standard interactive brushing of a parallel coordinates plot. We introduce two new interaction concepts: Higher-order, sketch-based brushing, and smart, data-driven brushing. Higher-order brushes support interactive, flexible, n-dimensional pattern searches involving an arbitrary number of dimensions. Smart, data-driven brushing provides interactive, real-time guidance to the user during the brushing process based on derived meta-data. In addition, we implement a selection of novel enhancements and user options that complement the two techniques as well as enhance the exploration and analytical ability of the user. We demonstrate the utility and evaluate the results using a case study with a large, high-dimensional, real-world telecommunication data set and we report domain expert feedback from the data suppliers.

Citation

Roberts, R. C., Laramee, R. S., Smith, G. A., Brookes, P., & D'Cruze, T. (2019). Smart Brushing for Parallel Coordinates. IEEE Transactions on Visualization and Computer Graphics, 25(3), 1575-1590. https://doi.org/10.1109/tvcg.2018.2808969

• Journal Article Type: Article
• Acceptance Date: Jan 1, 2018
• Online Publication Date: Feb 27, 2018
• Publication Date: Mar 1, 2019
• Deposit Date: Jan 15, 2021
• Publicly Available Date: Jan 21, 2021
• Journal: IEEE Transactions on Visualization and Computer Graphics
• Print ISSN: 1077-2626
• Electronic ISSN: 1941-0506
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 25
• Issue: 3
• Pages: 1575-1590
• DOI: https://doi.org/10.1109/tvcg.2018.2808969
• Keywords: Signal Processing; Software; Computer Vision and Pattern Recognition; Computer Graphics and Computer-Aided Design
• Public URL: https://nottingham-repository.worktribe.com/output/4571442
• Publisher URL: https://ieeexplore.ieee.org/document/8302598
• Additional Information: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.