The Connected Scatterplot for Presenting Paired Time Series
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This document describes research on the Connected Scatterplot (CS) technique for visually presenting paired time series data. The CS uses dots connected by lines and arrows to show the relationship between two time-varying datasets over time. User studies found that the CS was generally understandable but performed better with explicit labels about the axes and flow of time. It was also better at depicting changing patterns than the traditional Dual-Axis Line Chart, but had limitations for extremely complex data patterns. Guidelines are provided for designing effective CS visualizations.
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The Connected Scatterplot for Presenting Paired Time Series
- 1. The Connected Scatterplot for Presenting Paired Time Series Steve Haroz, Robert Kosara, and Steven L. Franconeri Kuan-Lin Tung 2014
- 2. The New York Times in February 2008
- 3. The New York Times in February 2008
- 4. The New York Times in February 2008
- 5. The New York Times in February 2012
- 6. The New York Times in February 2012
- 7. The New York Times in February 2012
- 8. The New York Times in February 2012
- 9. The New York Times in February 2012
- 10. Understandable and engaging ? 1. Relationship between data 2. Understandability 3. Connected Scatterplot (CS) V.S.Dual-axis line Chart(DALC)
- 14. Components Dot
- 15. Components Line
- 16. Components Arrow
- 17. Back to DALC ?
- 18. ?
- 20. Time Series
- 21. Graph Pattern No change, Slope, Loop
- 27. Limitations fixed intervals extremely complex shapes
- 28. Extremely Complex Example: TSMC 2330 20150915 Price Volume 20150916 > >
- 29. Study I Qualitatively Understanding The CS
- 32. Study II Axis Direction And Sequence
- 34. Animation or varying size over time might be able to mitigate this confusion.
- 38. The New York Times in February 2012
- 39. Guidelines • Give salient cues for the flow of time. • Give explicit reminders of two oriented axes. (Do better with annotations) • DALC is better for presenting correlation (Need more understanding) • Questions about complexity: Having a small number of unique shapes and features will likely make for a more memorable and understandable graph • Good for tracing and interacting with timeline (better with animation)