Stroscope: Multi-Scale Visualization of Irregularly Measured Time-Series Data
| Autor: | Jinwook Seo, Myoungsu Cho, Bohyoung Kim, Hee-Joon Bae |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Computer science
business.industry Bar chart Graph theory computer.software_genre Computer Graphics and Computer-Aided Design Graph law.invention Visualization Data visualization law Signal Processing Line graph Graph (abstract data type) Computer Vision and Pattern Recognition Data mining Time series business computer Software |
| Zdroj: | IEEE Transactions on Visualization and Computer Graphics. 20:808-821 |
| ISSN: | 1077-2626 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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