Provenance for Interactive Visualizations
Fotis Psallidas, Eugene Wu
TL;DR
This paper explores how data provenance can be integrated into interactive visualizations, demonstrating that interactions can be expressed through provenance and systems can be extended with new interactions.
Contribution
It introduces a method to incorporate data provenance into interactive visualizations, enabling easy extension with novel interactions.
Findings
Interactions are expressible in terms of provenance.
Provenance-aware systems can be extended with new interactions.
The approach facilitates better understanding of data transformations.
Abstract
We highlight the connections between data provenance and interactive visualizations. To do so, we first incrementally add interactions to a visualization and show how these interactions are readily expressible in terms of provenance. We then describe how an interactive visualization system that natively supports provenance can be easily extended with novel interactions.
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Taxonomy
TopicsData Visualization and Analytics · Scientific Computing and Data Management · Time Series Analysis and Forecasting