Visual interaction with dimensionality reduction: a structured literature analysis

Sacha, Dominik and Zhang, Leishi and Sedlmair, Michael and Lee, John A. and Peltonen, Jaakko and Weiskopf, Daniel and North, Stephen C. and Keim, Daniel A. (2017) Visual interaction with dimensionality reduction: a structured literature analysis. IEEE Transactions on Visualization and Computer Graphics, 23 (1). pp. 241-250. ISSN 1077-2626

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Abstract

Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data. For DR techniques to be useful in exploratory data analysis, they need to be adapted to human needs and domain-specific problems, ideally, interactively, and on-the-fly. Many visual analytics systems have already demonstrated the benefits of tightly integrating DR with interactive visualizations. Nevertheless, a general, structured understanding of this integration is missing. To address this, we systematically studied the visual analytics and visualization literature to investigate how analysts interact with automatic DR techniques. The results reveal seven common interaction scenarios that are amenable to interactive control such as specifying algorithmic constraints, selecting relevant features, or choosing among several DR algorithms. We investigate specific implementations of visual analysis systems integrating DR, and analyze ways that other machine learning methods have been combined with DR. Summarizing the results in a “human in the loop” process model provides a general lens for the evaluation of visual interactive DR systems. We apply the proposed model to study and classify several systems previously described in the literature, and to derive future research opportunities.

Item Type: Article
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 20254
Notes on copyright: © 2016 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.
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Depositing User: Leishi Zhang
Date Deposited: 27 Jul 2016 11:15
Last Modified: 15 Sep 2017 11:50
URI: http://eprints.mdx.ac.uk/id/eprint/20254

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