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Journal article 524 views 23 downloads

Can animation support the visualisation of dynamic graphs? / Daniel Archambault; Helen C. Purchase

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

Swansea University Author: Archambault, Daniel

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
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa20860
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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 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.
College: College of Science
Start Page: 495
End Page: 509