Tubes or Ribbons? Comparing Texture‐space Visualization for Multivariate Line Data

Abstract Multivariate line data is critical for analyzing flow fields, agent systems, and dynamic trajectories. Embedding secondary variables along spatial paths using surface‐based primitives such as ribbons and circular tubes introduces challenges related to perspective, scale, and distortion. Perceptual trade‐offs due to these challenges remain unclear. We address this gap through a controlled user study with 10 experts in computational fluid dynamics and visualization, performing four identical analysis tasks involving both spatial (requiring location‐based relationships) and non‐spatial (requiring attribute value comparisons) aspects. The tasks were performed using a prototype with interactivity limited to controlling the camera. While quantitative measures showed no significant performance differences between embedded visualizations on ribbons and tubes, we found a clear subjective preference for tubes among the study participants. Furthermore, their feedback indicates surface‐based embeddings are generally helpful and should be utilized more often.