Watch+Strap: Extending Smartwatches with Interactive StrapDisplays

Klamka, Konstantin; Horak, Tom; Dachselt, Raimund

doi:10.1145/3313831.3376199

Cited by 18 publications

(12 citation statements)

References 70 publications

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“…First, we re-create an example publication from IEEE VIS 2018 [35] with SSVG which was originally implemented with canvas, demonstrating that work which typically happens offline or in complex Canvas or WebGL environments can be implemented and shared in the D3.js and SVG format which is better understood by the community. Second, we show how SSVG was used in a CHI 2020 visualization publication to render visualizations on wrist bands of smart watches [23]. Finally, on a IEEE VIS authorship network visualization, we demonstrate that expanding the scope of SVG enables visualization creators to focus on visual marks during development.…”

Section: Utilitymentioning

confidence: 95%

“…11). Finally, we show SSVG's applicability in visualization research in a real-world research project that uses SSVG published at CHI 2020 by Klamka, Horak and Dachselt, researchers unaffiliated with the authors [23].…”

Section: Fpsmentioning

confidence: 99%

“…Klamka et. al used SSVG to efficiently render data visualizations on e-Ink devices [23], which can render images but not SVG. The researchers implemented their data visualizations using SVG and D3.js, their preferred technologies, and use SSVG to render images on the devices.…”

Section: E-ink Data Visualizationmentioning

confidence: 99%

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Scalable Scalable Vector Graphics: Automatic Translation of Interactive SVGs to a Multithread VDOM for Fast Rendering

Schwab

Saffo

Bond

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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The dominant markup language for Web visualizations-Scalable Vector Graphics (SVG)-is comparatively easy to learn, and is open, accessible, customizable via CSS, and searchable via the DOM, with easy interaction handling and debugging. Because these attributes allow visualization creators to focus on design on implementation details, tools built on top of SVG, such as D3.js, are essential to the visualization community. However, slow SVG rendering can limit designs by effectively capping the number of on-screen data points, and this can force visualization creators to switch to Canvas or WebGL. These are less flexible (e.g., no search or styling via CSS), and harder to learn. We introduce Scalable Scalable Vector Graphics (SSVG) to reduce these limitations and allow complex and smooth visualizations to be created with SVG. SSVG automatically translates interactive SVG visualizations into a dynamic virtual DOM (VDOM) to bypass the browser's slow 'to specification' rendering by intercepting JavaScript function calls. De-coupling the SVG visualization specification from SVG rendering, and obtaining a dynamic VDOM, creates flexibility and opportunity for visualization system research. SSVG uses this flexibility to free up the main thread for more interactivity and renders the visualization with Canvas or WebGL on a web worker. Together, these concepts create a drop-in JavaScript library which can improve rendering performance by 3-9× with only one line of code added. To demonstrate applicability, we describe the use of SSVG on multiple example visualizations including published visualization research. A free copy of this paper, collected data, and source code are available as open science at osf.io/ge8wp.

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Section: Utilitymentioning

confidence: 95%

Section: Fpsmentioning

confidence: 99%

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Scalable Scalable Vector Graphics: Automatic Translation of Interactive SVGs to a Multithread VDOM for Fast Rendering

Schwab

Saffo

Bond

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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“…Others' visualization research described novel visualization designs specifically for smartwatches. Examples include research on representing health and fitness data on smartwatches [2,18], for line charts [19], temporal data [27], activity tracking more broadly [9], and even for integrating visualizations in watch straps [12]. In contrast to these works, our study contributes information on people's current representation types on watch faces and the results can be used to inform future research such as reported above.…”

Section: Related Workmentioning

confidence: 99%

Visualizing information on watch faces: A survey with smartwatch users

Islam¹,

Bezerianos²,

Lee³

et al. 2020

Preprint

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Watch battery level Calories burned Distance traveled Heart rate/ECG waveform Step count Weather info Temperature Figure 1: Smartwatch face examples (from Facer [13]) with increasing amounts of data items and representation types. From left to right: Material Volcano (BlueIceshard), Pie Charts II (Sunny Liao), Minimal Colors H (AK Watch), and Earthshade (Brad C). The graph on the right shows common pairs of data types displayed on the watch faces our 237 survey participants used.

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“…Furthermore, research on mobile data visualization is sparse [48]. Much of the mobile visualization research has been carried out with tablets [10], and only a handful of projects have recently begun to study data visualizations on smartphones (e.g., [11,12,61]) and smartwatches (e.g., [9,13,46]).…”

Section: Introductionmentioning

confidence: 99%

Data@Hand: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction

Kim

Lee

Srinivasan

et al. 2021

Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

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Figure 1: Data@Hand supports multimodal interactions to enable people to easily navigate and compare their personal health data on smartphones. People can execute a context-agnostic command such as setting up a comparison by specifying two new periods using a global speech button ○ 1 . They can feed a context to their utterance by touch, such as the start date ○ 2 , the target for comparison ○ 3 , or the time range for refning the view ○ 4 .

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Watch+Strap: Extending Smartwatches with Interactive StrapDisplays

Cited by 18 publications

References 70 publications

Scalable Scalable Vector Graphics: Automatic Translation of Interactive SVGs to a Multithread VDOM for Fast Rendering

Scalable Scalable Vector Graphics: Automatic Translation of Interactive SVGs to a Multithread VDOM for Fast Rendering

Visualizing information on watch faces: A survey with smartwatch users

Data@Hand: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction

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