Evaluation on interactive visualization data with scatterplots

Huang, ML; Nguyen, QV; Miller, N; Arness, D; Huang, W; Simoff, S

Evaluation on interactive visualization data with scatterplots

Huang, ML Nguyen, QV Miller, N Arness, D Huang, W Simoff, S

Permalink

Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Visual Informatics, 2020, 4, (4), pp. 1-1
Issue Date:: 2020-09-26

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published versionAdobe PDF (1.92 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Huang, ML
dc.contributor.author	Nguyen, QV
dc.contributor.author	Miller, N
dc.contributor.author	Arness, D
dc.contributor.author	Huang, W
dc.contributor.author	Simoff, S
dc.date.accessioned	2020-10-25T03:43:52Z
dc.date.available	2020-09-20
dc.date.available	2020-10-25T03:43:52Z
dc.date.issued	2020-09-26
dc.identifier.citation	Visual Informatics, 2020, 4, (4), pp. 1-1
dc.identifier.issn	2468-502X
dc.identifier.uri	http://hdl.handle.net/10453/143519
dc.description.abstract	Scatterplots and scatterplot matrix methods have been popularly used for showing statistical graphics and for exposing patterns in multivariate data. A recent technique, called Linkable Scatterplots, provides an interesting idea for interactive visual exploration which provides a set of necessary plot panels on demand together with interaction, linking and brushing. This article presents a controlled study with a mixed-model design to evaluate the effectiveness and user experience on the visual exploration when using a Sequential-Scatterplots who a single plot is shown at a time, Multiple-Scatterplots who number of plots can be specified and shown, and Simultaneous-Scatterplots who all plots are shown as a scatterplot matrix. Results from the study demonstrated higher accuracy using the Multiple-Scatterplots visualization, particularly in comparison with the Simultaneous-Scatterplots. While the time taken to complete tasks was longer in the Multiple-Scatterplots technique, compared with the simpler Sequential-Scatterplots, Multiple-Scatterplots is inherently more accurate. Moreover, the Multiple-Scatterplots technique is the most highly preferred and positively experienced technique in this study. Overall, results support the strength of Multiple-Scatterplots and highlight its potential as an effective data visualization technique for exploring multivariate data.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Visual Informatics
dc.relation.isbasedon	https://doi.org/10.1016/j.visinf.2020.09.004	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	Elsevier required licence: © 2020 . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. The definitive publisher version is available online at https://doi.org/10.1016/j.visinf.2020.09.004	en_US
dc.rights	Under a Creative Commons license
dc.title	Evaluation on interactive visualization data with scatterplots
dc.type	Journal Article
utslib.citation.volume	4
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	open_access	*
pubs.consider-herdc	true
dc.date.updated	2020-10-25T03:43:36Z
pubs.issue	4
pubs.publication-status	Published online
pubs.volume	4
utslib.citation.issue	4

Abstract:

Scatterplots and scatterplot matrix methods have been popularly used for showing statistical graphics and for exposing patterns in multivariate data. A recent technique, called Linkable Scatterplots, provides an interesting idea for interactive visual exploration which provides a set of necessary plot panels on demand together with interaction, linking and brushing. This article presents a controlled study with a mixed-model design to evaluate the effectiveness and user experience on the visual exploration when using a Sequential-Scatterplots who a single plot is shown at a time, Multiple-Scatterplots who number of plots can be specified and shown, and Simultaneous-Scatterplots who all plots are shown as a scatterplot matrix. Results from the study demonstrated higher accuracy using the Multiple-Scatterplots visualization, particularly in comparison with the Simultaneous-Scatterplots. While the time taken to complete tasks was longer in the Multiple-Scatterplots technique, compared with the simpler Sequential-Scatterplots, Multiple-Scatterplots is inherently more accurate. Moreover, the Multiple-Scatterplots technique is the most highly preferred and positively experienced technique in this study. Overall, results support the strength of Multiple-Scatterplots and highlight its potential as an effective data visualization technique for exploring multivariate data.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/143519