Mosaic: An Architecture for Scalable & Interoperable Data Views

Mosaic is an architecture for greater scalability, extensibility, and interoperability of interactive data views. Mosaic decouples data processing from specification logic: clients publish their data needs as declarative queries that are then managed and optimized by a coordinator that proxies access to a scalable data store. Mosaic generalizes Vega-Lite's selection abstraction to enable rich integration and linking of both standalone components (including menus, text search, and tables) and visualizations created using vgplot, a grammar of interactive graphics in which graphical marks act as Mosaic clients. We demonstrate Mosaic's expressiveness, extensibility, and interoperability through examples that compose diverse visualization, interaction, and optimization techniques. To evaluate scalability, we present benchmark studies with order-of-magnitude performance improvements over existing web-based visualization systems -- enabling flexible, real-time visual exploration of billion+ record datasets. We conclude by discussing Mosaic's potential as an open platform that bridges visualization languages, scalable visualization, and interactive data systems more broadly.