eCite Digital Repository

Visual performance in multidimensional data characterisation with scatterplots and parallel coordinates


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]


Copyright Statement

Copyright 2016 Society for Imaging Science and Technology.

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


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:Computer vision and multimedia computation
Research Field:Pattern recognition
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Engelke, U (Dr Ulrich Engelke)
ID Code:120044
Year Published:2016
Deposited By:Information and Communication Technology
Deposited On:2017-08-09
Last Modified:2017-09-28
Downloads:118 View Download Statistics

Repository Staff Only: item control page