User-Defined Interactions for Visual Data Exploration With the Combination of Smartwatch and Large Display

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Abstract

The process of visual analytics is composed of the visual data exploration tasks supporting analytical reasoning. When performing analytical tasks with the interactive visual interfaces displayed by the large screen, physical discomforts such as gorilla-arm effect can be easily caused. To enrich the input space for analysts, there has been some researches concerning the cross-device analysis combining mobile devices with the large display. Although the effectiveness of expert-level designs has been demonstrated, little is known of the ordinary users' preferences for using a mobile device to issue commands, especially the small one like smartwatch. We implement a three-stage study to investigate and validate these preferences. A total of 181 distinctive gestural inputs and 52 interface designs for 21 tasks were collected from analysts. Expert designers selected the best practices from these user-defined interactions. A performance test was subsequently developed to assess the selected interactions in terms of quantitative statistics and subjective ratings. Our work provides empirical support and proposes a set of design guidelines for optimizing watch-based interactions aimed at remote control of visual data on the large display. Through this research, we hope to advance the development of smartwatches as visual analytics tools and provide visual analysts with a better usage experience.

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Xiao, Y., & Liu, L. (2024). User-Defined Interactions for Visual Data Exploration With the Combination of Smartwatch and Large Display. IEEE Access, 12, 78657–78679. https://doi.org/10.1109/ACCESS.2024.3404876

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