DataParticles is a natural language-oriented, block-based authoring tool for animated unit visualizations. Creators can author animated unit visualizations that are congruent with their story narratives by writing plain text in a rich text editor.
Unit visualizations have been widely used in data storytelling within interactive articles and videos. However, authoring data stories that contain animated unit visualizations is challenging due to the tedious, time-consuming process of switching back and forth between writing a narrative and configuring the accompanying visualizations and animations.
To streamline this process, we present DataParticles, a block-based story editor that leverages the latent connections between text, data, and visualizations to help creators flexibly prototype, explore, and iterate on a story narrative and its corresponding visualizations.
To inform the design of DataParticles we studied a dataset of 44 existing animated unit visualizations to identify the narrative patterns and congruence principles they employed. A user study with experts showed that DataParticles can significantly simplify the process of authoring data stories with animated unit visualizations by encouraging exploration and supporting fast prototyping.
DataParticles uses a pipeline to generate AUVs by taking the visual states from the previous block and the text narration in the current block as input.
