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Glanceable Visualization: Studies of Data Comparison Performance on Smartwatches
Tanja Blascheck, Lonni Besançon, Anastasia Bezerianos, Bongshin Lee, Petra Isenberg

Glanceable Visualization: Studies of Data Comparison Performance on Smartwatches

Science & Mathematics Published 2019 Verification Pending

Overview & Synopsis

We present the results of two perception studies to assess how quickly people can perform a simple data comparison task for small-scale visualizations on a smartwatch. The main goal of these studies is to extend our understanding of design constraints for smartwatch visualizations. Previous work has shown that a vast majority of smartwatch interactions last under 5 s. It is still unknown what people can actually perceive from visualizations during such short glances, in particular with such a limited display space of smartwatches. To shed light on this question, we conducted two perception studies that assessed the lower bounds of task time for a simple data comparison task. We tested three chart types common on smartwatches: bar charts, donut charts, and radial bar charts with three different data sizes: 7, 12, and 24 data values. In our first study, we controlled the differences of the two target bars to be compared, while the second study varied the difference randomly. For both studies, we found that participants performed the task on average in

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Document Information

Document Title Glanceable Visualization: Studies of Data Comparison Performance on Smartwatches
Author / Organization Tanja Blascheck, Lonni Besançon, Anastasia Bezerianos, Bongshin Lee, Petra Isenberg
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2019
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-139942
Original Source Link Visit Source Page on hal.science »