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Tubes or Ribbons? Comparing Texture-space Visualization for Multivariate Line Data
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DOI：10.1111/cgf.70441.png)
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Abstract
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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.
Keywords:
CCS Concepts
• Human-centered computing → Empirical studies in visualization
Visualization techniques
Visualization design and evaluation methods
• Applied computing → Physical sciences and engineering
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