Visualizations as Data Input?

Date
2021-10-01
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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 datasets 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 characterizing 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.
Description
This manuscript was presented at alt.VIS, a workshop co-located with IEEE VIS 2021 (held virtually).
Keywords
Input Visualization, Visualization, Physicalization
Citation
Huron, S. and Willet, W. (2021, October 24-29). Visualizations as Data Input? [Conference presentation]. 2021 IEEE Conference on Visualization and Visual Analytics, Virtual Conference. http://ieeevis.org/year/2021/welcome