Interactive horizon graphs: Improving the compact visualization of multiple time series

Perin, C., Vernier, F. & Fekete, J. (2013). Interactive horizon graphs: Improving the compact visualization of multiple time series. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '13). (pp. 3217-3226). New York, NY, United States: ACM. ISBN 9781450318990

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Abstract

Many approaches have been proposed for the visualization of multiple time series. Two prominent approaches are reduced line charts (RLC), which display small multiples for time series, and the more recent horizon graphs (HG). We propose to unify RLC and HG using a new technique-interactive horizon graphs (IHG)- which uses pan and zoom interaction to increase the number of time series that can be analysed in parallel. In a user study we compared RLC, HG, and IHG across several tasks and numbers of time series, focusing on datasets with both large scale and small scale variations. Our results show that IHG outperform the other two techniques in complex comparison and matching tasks where the number of charts is large. In the hardest task IHG have a significantly higher number of good answers (correctness) than HG (+14%) and RLC (+51%) and a lower error magnitude than HG (-64%) and RLC (-86%). Copyright © 2013 ACM.

Item Type: Book Section
Additional Information: © ACM, 2013. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '13), http://doi.acm.org/10.1145/2470654.2466441
Uncontrolled Keywords: Visualization; Horizon Graphs; Time Series; Evaluation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Informatics > Department of Computing
URI: http://openaccess.city.ac.uk/id/eprint/16704

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