UW Interactive Data Lab
Arvind Satyanarayan, Ryan Russell, Jane Hoffswell, Jeffrey Heer
The Reactive Vega dataflow graph created from a declarative specification for a interactive index chart of streaming financial data. As streaming data arrives from the Yahoo! Finance API, or as a user moves their mouse pointer across the chart, an update cycle propagates through the graph and triggers an efficient update and re-render of the visualization.
We present Reactive Vega, a system architecture that provides the first robust and comprehensive treatment of declarative visual and interaction design for data visualization. Starting from a single declarative specification, Reactive Vega constructs a dataflow graph in which input data, scene graph elements, and interaction events are all treated as first-class streaming data sources. To support expressive interactive visualizations that may involve time-varying scalar, relational, or hierarchical data, Reactive Vega’s dataflow graph can dynamically re-write itself at runtime by extending or pruning branches in a data-driven fashion. We discuss both compile- and run-time optimizations applied within Reactive Vega, and share the results of benchmark studies that indicate superior interactive performance to both D3 and the original, non-reactive Vega system.
Arvind Satyanarayan, Ryan Russell, Jane Hoffswell, Jeffrey Heer
IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis), 2016