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Mosaic: An Architecture for Scalable & Interoperable Data Views
IEEE Transactions on Visualization and Computer Graphics
|October 26, 2023
Summary
Mosaic is a new architecture for scalable, interactive data visualization. It improves performance by decoupling data processing and optimizing queries for large datasets.
Area of Science:
- Computer Science
- Data Visualization
- Human-Computer Interaction
Background:
- Interactive data visualization systems often face scalability challenges.
- Integrating diverse data sources and interactive components can be complex.
Purpose of the Study:
- To introduce Mosaic, an architecture designed for enhanced scalability, extensibility, and interoperability of interactive data views.
- To demonstrate how Mosaic enables flexible and real-time exploration of large datasets.
Main Methods:
- Mosaic decouples data processing from specification logic using declarative queries.
- A coordinator manages and optimizes queries, proxying access to scalable data stores.
- Generalizes Vega-Lite's selection abstraction for cross-component linking.
Main Results:
- Mosaic achieves order-of-magnitude performance improvements over existing web-based visualization systems.
- Enables real-time visual exploration of datasets with billions of records.
- Demonstrates expressiveness and interoperability through diverse examples and vgplot integration.
Conclusions:
- Mosaic offers a scalable and extensible platform for interactive data visualization.
- It bridges visualization languages, scalable visualization techniques, and interactive data systems.
- Potential for broader applications in interactive data exploration and analysis.
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