Visualization

In digital spaces, people often struggle to intuitively grasp the qualities of a perfume—text descriptions can be long and tedious, underscoring the need for more visual and instantly understandable representations. To address this gap, we investigated a parametric visualization toolkit for communicating perfume qualities without the actual scent. A formative study explored which visual elements might best represent attributes, revealing commonly nominated features such as layers, stroke thickness, and curvature, and highlighting motion as a promising cue for dynamic characteristics. Building on these insights, we developed ParaScent, a toolkit that encodes perfume attributes into motion-enhanced visuals. In a user evaluation, ParaScent improved interpretation, stimulated curiosity, and increased confidence in scent selection compared to conventional static, chart-based visualizations. These findings point to the potential of motion-driven, multi-parameter representations as an engaging, accessible, and effective way to communicate scent in digital contexts.