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The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays

Alexandra Lee, Daniel Archambault Orcid Logo, Miguel A. Nacenta

IEEE Transactions on Visualization and Computer Graphics, Volume: 27, Issue: 2, Pages: 528 - 538

Swansea University Authors: Alexandra Lee, Daniel Archambault Orcid Logo

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DOI (Published version): 10.1109/tvcg.2020.3030446

Abstract

Dynamic networks can be challenging to analyze visually, especially if they span a large time range during which new nodes and edges can appear and disappear. Although it is straightforward to provide interfaces for visualization that represent multiple states of the network (i.e., multiple timeslic...

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Published in: IEEE Transactions on Visualization and Computer Graphics
ISSN: 1077-2626 2160-9306
Published: Institute of Electrical and Electronics Engineers (IEEE) 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa55105
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first_indexed 2020-09-01T10:00:22Z
last_indexed 2021-02-12T04:18:43Z
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spelling 2021-02-11T12:23:38.8267196 v2 55105 2020-09-01 The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays 7c6dc217555b0fea264ff0dd7d0aa374 Alexandra Lee Alexandra Lee true false 8fa6987716a22304ef04d3c3d50ef266 0000-0003-4978-8479 Daniel Archambault Daniel Archambault true false 2020-09-01 HDAT Dynamic networks can be challenging to analyze visually, especially if they span a large time range during which new nodes and edges can appear and disappear. Although it is straightforward to provide interfaces for visualization that represent multiple states of the network (i.e., multiple timeslices) either simultaneously (e.g., through small multiples) or interactively (e.g., through interactive animation), these interfaces might not support tasks in which disjoint timeslices need to be compared. Since these tasks are key for understanding the dynamic aspects of the network, understanding which interactive visualizations best support these tasks is important. We present the results of a series of laboratory experiments comparing two traditional approaches (small multiples and interactive animation), with a more recent approach based on interactive timeslicing. The tasks were performed on a large display through a touch interface. Participants completed 24 trials of three tasks with all techniques. The results show that interactive timeslicing brings benefit when comparing distant points in time, but less benefits when analyzing contiguous intervals of time. Journal Article IEEE Transactions on Visualization and Computer Graphics 27 2 528 538 Institute of Electrical and Electronics Engineers (IEEE) 1077-2626 2160-9306 1 2 2021 2021-02-01 10.1109/tvcg.2020.3030446 COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University 2021-02-11T12:23:38.8267196 2020-09-01T10:52:10.8827244 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Alexandra Lee 1 Daniel Archambault 0000-0003-4978-8479 2 Miguel A. Nacenta 3 55105__18094__7dde87dcba2e436a8c2a4a779666fdaf.pdf An_experimental_evaluation_of_interfaces_for_the_visual_exploration_of_dynamic_network_data_using_large_touch_screen_wall_displays (1).pdf 2020-09-01T10:54:55.3394159 Output 3608442 application/pdf Accepted Manuscript true true eng
title The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays
spellingShingle The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays
Alexandra Lee
Daniel Archambault
title_short The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays
title_full The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays
title_fullStr The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays
title_full_unstemmed The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays
title_sort The Effectiveness of Interactive Visualization Techniques for Time Navigation of Dynamic Graphs on Large Displays
author_id_str_mv 7c6dc217555b0fea264ff0dd7d0aa374
8fa6987716a22304ef04d3c3d50ef266
author_id_fullname_str_mv 7c6dc217555b0fea264ff0dd7d0aa374_***_Alexandra Lee
8fa6987716a22304ef04d3c3d50ef266_***_Daniel Archambault
author Alexandra Lee
Daniel Archambault
author2 Alexandra Lee
Daniel Archambault
Miguel A. Nacenta
format Journal article
container_title IEEE Transactions on Visualization and Computer Graphics
container_volume 27
container_issue 2
container_start_page 528
publishDate 2021
institution Swansea University
issn 1077-2626
2160-9306
doi_str_mv 10.1109/tvcg.2020.3030446
publisher Institute of Electrical and Electronics Engineers (IEEE)
college_str Faculty of Science and Engineering
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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 Dynamic networks can be challenging to analyze visually, especially if they span a large time range during which new nodes and edges can appear and disappear. Although it is straightforward to provide interfaces for visualization that represent multiple states of the network (i.e., multiple timeslices) either simultaneously (e.g., through small multiples) or interactively (e.g., through interactive animation), these interfaces might not support tasks in which disjoint timeslices need to be compared. Since these tasks are key for understanding the dynamic aspects of the network, understanding which interactive visualizations best support these tasks is important. We present the results of a series of laboratory experiments comparing two traditional approaches (small multiples and interactive animation), with a more recent approach based on interactive timeslicing. The tasks were performed on a large display through a touch interface. Participants completed 24 trials of three tasks with all techniques. The results show that interactive timeslicing brings benefit when comparing distant points in time, but less benefits when analyzing contiguous intervals of time.
published_date 2021-02-01T04:09:05Z
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score 10.998228

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