Input Visualization: Collecting and Modifying Data with Visual Representations - Equipe Interaction, Technologies, Activités Access content directly
Conference Papers Year : 2024

Input Visualization: Collecting and Modifying Data with Visual Representations

Visualisation à entrées d'information : Collecter et modifier des données à l'aide de représentations visuelles


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.
Fichier principal
Vignette du fichier
InputVisualization-CHI2024-AuthorVersion.pdf (6.19 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04558867 , version 1 (26-04-2024)



Nathalie Bressa, Jordan Louis, Wesley Willett, Samuel Huron. Input Visualization: Collecting and Modifying Data with Visual Representations. The ACM Conference on Human Factors in Computing Systems, 2024, Honolulu, France. ⟨10.1145/3613904.3642808⟩. ⟨hal-04558867⟩
132 View
78 Download



Gmail Mastodon Facebook X LinkedIn More