Time sequences

  • Authors:
  • Ross Shannon;Aaron Quigley;Paddy Nixon

  • Affiliations:
  • UCD Dublin, Dublin, Ireland;UCD Dublin, Dublin, Ireland;UCD Dublin, Dublin, Ireland

  • Venue:
  • CHI '09 Extended Abstracts on Human Factors in Computing Systems
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

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.