DataSway: Vivifying Metaphoric Visualization with Animation Clip Generation and Coordination
For designers and researchers creating animated data visualizations, DataSway provides a novel human-AI workflow that reduces the complexity of crafting metaphor-aligned animations, though the approach is incremental as it builds on existing VLM and timeline coordination techniques.
DataSway enables creators to animate metaphoric visualizations by generating animation clips from vision-language models and coordinating timelines based on data attributes, addressing challenges in semantic alignment, data fidelity, and interactivity. A user study (N=14) showed improved creativity support and usability, with a gallery of seven cases demonstrating its capabilities.
Animating metaphoric visualizations brings data to life, enhancing the comprehension of abstract data encodings and fostering deeper engagement. However, creators face significant challenges in designing these animations, such as crafting motions that align semantically with the metaphors, maintaining faithful data representation during animation, and seamlessly integrating interactivity. We propose a human-AI co-creation workflow that facilitates creating animations for SVG-based metaphoric visualizations. Users can initially derive animation clips for data elements from vision-language models (VLMs) and subsequently coordinate their timelines based on entity order, attribute values, spatial layout, or randomness. Our design decisions were informed by a formative study with experienced designers (N=8). We further developed a prototype, DataSway, and conducted a user study (N=14) to evaluate its creativity support and usability. A gallery with seven cases demonstrates its capabilities and applications in web-based hypermedia. We conclude with implications for future research on bespoke data visualization animation.