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.
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.