Multi-scale Visualization of Irregularly Measured Time-series Data
Myoungsu Cho, Bohyoung Kim, Hee-Joon Bae, and Jinwook Seo / 2013
- Myoungsu Cho, Seoul National University, Seoul, Republic of Korea
- Bohyoung Kim, Hankuk University of Foreign Studies, Yongin-si, Republic of Korea
- Hee-Joon Bae, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Jinwook Seo, Seoul National University, Seoul, Republic of Korea
For irregularly measured time-series data, the measurement frequency or interval is as crucial information as measurements are. A well-known time-series visualization such as the line graph is good at showing an overall temporal pattern of change; however, it is not so effective in revealing the measurement frequency/interval while likely giving illusory confidence in values between measurements. In contrast, the bar graph is more effective in showing the frequency/interval, but less effective in showing an overall pattern than the line graph. We integrate the line graph and bar graph in a unified visualization model, called a ripple graph, to take the benefits of both of them with enhanced graphical integrity. Based on the ripple graph, we implemented an interactive time-series data visualization tool, called Stroscope, which facilitates multi-scale visualizations by providing users with a graphical widget to interactively control the integrated visualization model. We evaluated the visualization model (i.e. the ripple graph) through a controlled user study and Stroscope through long-term case studies with neurologists exploring large blood pressure measurement data of stroke patients. Results from our evaluations demonstrate that the ripple graph outperforms existing time-series visualizations, and that Stroscope has the efficacy and potential as an effective visual analysis tool for (irregularly) measured time-series data.
This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korean Government (MSIP) (No. 2011-0030813, No. 2010-0002266 and NRF-2013R1A1A3006706). The ICT at Seoul National University provided research facilities for this study.