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Visual performance in multidimensional data characterisation with scatterplots and parallel coordinates

Citation

Engelke, U and Vuong, J and Heinrich, J, Visual performance in multidimensional data characterisation with scatterplots and parallel coordinates, Human Vision and Electronic Imaging 2016, 14-18 February 2016, San Francisco, USA, pp. 288-293. ISBN 9781510827943 (2016) [Refereed Conference Paper]


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Copyright Statement

Copyright 2016 Society for Imaging Science and Technology.

DOI: doi:10.2352/ISSN.2470-1173.2016.16.HVEI-136

Abstract

We present a study on the visual assessment of relative data point distances in Parallel coordinate systems and scatterpiots in Cartesian coordinate systems Specifically, we assess the impact of coordinate system type, dimension, and relative point distance deviation. We performed an online pilot experiment with 100 participants using Amazon's MechanicalTurk. The experiment design and methodology are presented in detail and results indicate that there may indeed be a difference in human performance when visually assessing distances in the considered coordinate systems. We argue that further investigations are needed to draw stronger conclusions. These should consider inclusion of other factors into the experiment design, such as the relative angle between data points that is expected to have a significant impact on the outcomes.

Item Details

Item Type:Refereed Conference Paper
Keywords:cartesian coordinate system, co-ordinate system, experiment design, human performance, multidimensional data
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Pattern Recognition and Data Mining
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Information Processing Services (incl. Data Entry and Capture)
Author:Engelke, U (Dr Ulrich Engelke)
ID Code:120044
Year Published:2016
Deposited By:Computing and Information Systems
Deposited On:2017-08-09
Last Modified:2017-09-28
Downloads:7 View Download Statistics

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