IEEE VIS 2024 Content: Design-Specific Transforms In Visualization

Design-Specific Transforms In Visualization

eugene Wu - Columbia University, New York City, United States

Remco Chang - Tufts University, Medford, United States

Room: Bayshore I

2024-10-14T16:00:00ZGMT-0600Change your timezone on the schedule page
2024-10-14T16:00:00Z
Exemplar figure, described by caption below
We propose to extend the Infovis Reference Model to explicitly model the role of design-specific data transformations in visualization design. This model decomposes visual mappings into design-specific transformations (e.g., stacking, quantization, calculating statistics) and a visual encoding. We further propose to model tasks as functions over the input data that the user wishes to estimate using the visualization.
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Abstract

In visualization, the process of transforming raw data into visually comprehensible representations is pivotal. While existing models like the Information Visualization Reference Model describe the data-to-visual mapping process, they often overlook a crucial intermediary step: design-specific transformations. This process, occurring after data transformation but before visual-data mapping, further derives data, such as groupings, layout, and statistics, that are essential to properly render the visualization. In this paper, we advocate for a deeper exploration of design-specific transformations, highlighting their importance in understanding visualization properties, particularly in relation to user tasks. We incorporate design-specific transformations into the Information Visualization Reference Model and propose a new formalism that encompasses the user task as a function over data. The resulting formalism offers three key benefits over existing visualization models: (1) describing tasks as compositions of functions, (2) enabling analysis of data transformations for visual-data mapping, and (3) empowering reasoning about visualization correctness and effectiveness. We further discuss the potential implications of this model on visualization theory and visualization experiment design.