Input Visualization: Collecting and Modifying Data with Visual Representations

要旨

We examine input visualizations, visual representations that are designed to collect (and represent) new data rather than encode preexisting datasets. Information visualization is commonly used to reveal insights and stories within existing data. As a result, most contemporary visualization approaches assume existing datasets as the starting point for design, through which that data is mapped to visual encodings. Meanwhile, the implications of visualizations as inputs and as data sources have received little attention—despite the existence of visual and physical examples stretching back centuries. In this paper, we present a design space of 50 input visualizations analyzing their visual representation, data, artifact, context, and input. Based on this, we identify input modalities, purposes of input visualizations, and a set of design considerations. Finally, we discuss the relationship between input visualization and traditional visualization design and suggest opportunities for future research to better understand these visual representations and their potential.

著者
Nathalie Bressa
Télécom Paris, IP Paris, Palaiseau, France
Jordan Louis
Télécom Paris, Palaiseau, France
Wesley Willett
University of Calgary, Calgary, Alberta, Canada
Samuel Huron
Télécom Paris, Institut Polytechnique de Paris, Palaiseau, ile de France, France
論文URL

doi.org/10.1145/3613904.3642808

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Remote Presentations: Highlight on Design and Design Methods

Remote Sessions
8 件の発表
2024-05-14 18:00:00
2024-05-15 02:20:00