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Visualizations as Data Input?

Abstract : We examine ``input visualizations'', visual representations that are designed to collect (and represent) new data rather than encode pre-existing datasets. Information visualization is commonly used to reveal insights and stories within existing data. As a result, most contemporary visualization approaches assume existing data sets or data structures as the starting point for design, through which that data will be mapped to visual encodings to produce final visualizations. Meanwhile, the implications of visualizations as inputs and as data sources have received extremely little attention---despite the existence of visual and physical examples stretching back centuries---and the benefits, trades-offs, design patterns, and even the language necessary to describe them remain unexplored. In this paper we argue for the deeper examination of input visualizations, highlighting a set of recent examples and introducing vocabulary for describing them. Finally, we present a series of provocations which examine some of the challenges posed by input visualizations and suggest opportunities for better understanding this type of visual representations and their potential.
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Preprints, Working Papers, ...
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Contributor : Samuel Huron Connect in order to contact the contributor
Submitted on : Tuesday, September 28, 2021 - 11:02:36 AM
Last modification on : Sunday, June 26, 2022 - 3:13:58 AM
Long-term archiving on: : Wednesday, December 29, 2021 - 6:20:55 PM


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  • HAL Id : hal-03356575, version 1


Samuel Huron, Wesley Willett. Visualizations as Data Input?. 2021. ⟨hal-03356575⟩



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