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Can animation support the visualisation of dynamic graphs?

Daniel Archambault Orcid Logo, Helen C. Purchase

Information Sciences, Volume: 330, Pages: 495 - 509

Swansea University Author: Daniel Archambault Orcid Logo

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DOI (Published version): 10.1016/j.ins.2015.04.017

Abstract

Animation and small multiples are methods for visualizing dynamically evolving graphs. Animations present an interactive movie of the data where positions of nodes are smoothly interpolated as the graph evolves. Nodes fade in/out as they are added/removed from the data set. Small multiples presents...

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Published in: Information Sciences
ISSN: 00200255
Published: 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa20860
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first_indexed 2015-04-25T02:08:16Z
last_indexed 2019-07-17T20:16:35Z
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spelling 2019-07-17T15:11:36.1651561 v2 20860 2015-04-24 Can animation support the visualisation of dynamic graphs? 8fa6987716a22304ef04d3c3d50ef266 0000-0003-4978-8479 Daniel Archambault Daniel Archambault true false 2015-04-24 SCS Animation and small multiples are methods for visualizing dynamically evolving graphs. Animations present an interactive movie of the data where positions of nodes are smoothly interpolated as the graph evolves. Nodes fade in/out as they are added/removed from the data set. Small multiples presents the data like a comic book with the graph at various states in separate windows. The user scans these windows to see how the data evolves. In a recent experiment, drawing stability (known more widely as the “mental map”) was shown to help users follow specific nodes or long paths in dynamically evolving data. However, no significant difference between animation and small multiples presentations was found. In this paper, we look at data where the nodes in the graph have low drawing stability and analyze it with new error metrics: measuring how close the given answer is from the correct answer on a continuous scale. We find evidence that when the stability of the drawing is low and important nodes in the task cannot be highlighted throughout the time series, animation can improve task performance when compared to the use of small multiples. Journal Article Information Sciences 330 495 509 00200255 10 2 2016 2016-02-10 10.1016/j.ins.2015.04.017 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2019-07-17T15:11:36.1651561 2015-04-24T11:50:00.8334992 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Daniel Archambault 0000-0003-4978-8479 1 Helen C. Purchase 2 0020860-28042015144237.pdf maplikeJournalSIR1.pdf 2015-04-28T14:42:37.5430000 Output 65349899 application/pdf Author's Original true 2016-04-17T00:00:00.0000000 true
title Can animation support the visualisation of dynamic graphs?
spellingShingle Can animation support the visualisation of dynamic graphs?
Daniel Archambault
title_short Can animation support the visualisation of dynamic graphs?
title_full Can animation support the visualisation of dynamic graphs?
title_fullStr Can animation support the visualisation of dynamic graphs?
title_full_unstemmed Can animation support the visualisation of dynamic graphs?
title_sort Can animation support the visualisation of dynamic graphs?
author_id_str_mv 8fa6987716a22304ef04d3c3d50ef266
author_id_fullname_str_mv 8fa6987716a22304ef04d3c3d50ef266_***_Daniel Archambault
author Daniel Archambault
author2 Daniel Archambault
Helen C. Purchase
format Journal article
container_title Information Sciences
container_volume 330
container_start_page 495
publishDate 2016
institution Swansea University
issn 00200255
doi_str_mv 10.1016/j.ins.2015.04.017
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
description Animation and small multiples are methods for visualizing dynamically evolving graphs. Animations present an interactive movie of the data where positions of nodes are smoothly interpolated as the graph evolves. Nodes fade in/out as they are added/removed from the data set. Small multiples presents the data like a comic book with the graph at various states in separate windows. The user scans these windows to see how the data evolves. In a recent experiment, drawing stability (known more widely as the “mental map”) was shown to help users follow specific nodes or long paths in dynamically evolving data. However, no significant difference between animation and small multiples presentations was found. In this paper, we look at data where the nodes in the graph have low drawing stability and analyze it with new error metrics: measuring how close the given answer is from the correct answer on a continuous scale. We find evidence that when the stability of the drawing is low and important nodes in the task cannot be highlighted throughout the time series, animation can improve task performance when compared to the use of small multiples.
published_date 2016-02-10T03:24:42Z
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score 11.013371

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