Sizing the horizon

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Sizing the horizon: the effects of chart size and layering on the graphical perception of time series visualizations

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Conference on Human Factors in Computing Systems archive
Proceedings of the 27th international conference on Human factors in computing systems table of contents

Boston, MA, USA

SESSION: Visualization 2 table of contents

Pages 1303-1312

Year of Publication: 2009

ISBN:978-1-60558-246-7

Authors

Jeffrey Heer	Stanford University, Stanford, CA, USA
Nicholas Kong	University of California, Berkeley, Berkeley, CA, USA
Maneesh Agrawala	University of California, Berkeley, Berkeley, CA, USA

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery

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ACM New York, NY, USA

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Downloads (6 Weeks): 21, Downloads (12 Months): 226, Citation Count: 0

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ABSTRACT

We investigate techniques for visualizing time series data and evaluate their effect in value comparison tasks. We compare line charts with horizon graphs - a space-efficient time series visualization technique - across a range of chart sizes, measuring the speed and accuracy of subjects' estimates of value differences between charts. We identify transition points at which reducing the chart height results in significantly differing drops in estimation accuracy across the compared chart types, and we find optimal positions in the speed-accuracy tradeoff curve at which viewers performed quickly without attendant drops in accuracy. Based on these results, we propose approaches for increasing data density that optimize graphical perception.

REFERENCES

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