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extended-abstract

Time sequences

Published: 04 April 2009 Publication History

Abstract

Visualisations of dynamic data change in appearance over time, reflecting changes in the underlying data, be that the development of a social network, or the addition or removal of a device node in an ad-hoc communications network. As viewers of these visualisation tools, it is up to us to accurately perceive and keep up with the constantly shifting view, mentally noting as visual elements are added, removed, changed and rearranged, sometimes at great pace. In a complex data set with a lot happening, this can be a strain on the observer's comprehension, with changes in layout and visual population disrupting their internalised "mental model" of the data, leading to errors in perception. We present Time Sequences, a novel dual visualisation technique which dilates the flow of time in the visualisation so that observers are given proportionally more time to understand changes based on the density of activity in the visualisation.

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cover image ACM Conferences
CHI EA '09: CHI '09 Extended Abstracts on Human Factors in Computing Systems
April 2009
2470 pages
ISBN:9781605582474
DOI:10.1145/1520340
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 04 April 2009

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Author Tags

  1. dynamic data
  2. human factors
  3. perception
  4. visual analytics
  5. visualization

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CHI '09
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CHI EA '09 Paper Acceptance Rate 385 of 1,130 submissions, 34%;
Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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