Community edits over time reveal how online charts evolve
Beyond Initial Creation: Two Decades of Community-based Chart Revisions from Wikimedia Commons
Human-Computer Interaction
Summary
How do people together improve charts over time on Wikipedia's image site? The authors studied nearly 8,000 edits to over 1,600 chart images to find out. They saw that when many people edit, they focus more on style and text rather than data. Also, charts made as SVG files get more contributors but smaller, more focused changes than image files. This work helps us understand how collaborative editing changes visual information.
What this means in practice
- •For open source platform managers: Identify patterns of collaborative image edits to improve tools for chart version control and user contributions.
- •For data visualization teams: Design workflows that prioritize mark and text edits during active revision bursts to enhance chart clarity and accuracy in shared projects.
Authors
Jasmine Y. Shih, Chase Stokes, Melanie Tory, Marti Hearst
Abstract
Open online communities like Wikipedia offer a rich space for understanding the organic evolution of public-facing artifacts, but little is known about how these communities collectively edit chart images. We investigate the phenomenon of "community editing" of visualizations by exploring chart revision patterns on Wikimedia Commons. We introduce a novel dataset of 7,786 longitudinal chart revisions across 1,664 images, labeled with edit categories using an LLM pipeline. Initial data analysis uncovered several novel findings. Multi-contributor revision is associated with more edits to mark styling and text content compared to single-contributor revision. Temporally, mark and text edits occur in more "bursty" cadences than data edits. In addition, while SVG charts attract more unique contributors and revisions than raster charts, their edit histories involve more tightly scoped and less diverse changes. This dataset enables a wide range of analyses of chart change over time.