The Case for Data Visualization Management Systems [Vision Paper]

نویسندگان

  • Eugene Wu
  • Leilani Battle
  • Samuel R. Madden
چکیده

Most visualizations today are produced by retrieving data from a database and using a specialized visualization tool to render it. This decoupled approach results in significant duplication of functionality, such as aggregation and filters, and misses tremendous opportunities for cross-layer optimizations. In this paper, we present the case for an integrated Data Visualization Management System (DVMS) based on a declarative visualization language that fully compiles the end-to-end visualization pipeline into a set of relational algebra queries. Thus the DVMS can be both expressive via the visualization language, and performant by leveraging traditional and visualization-specific optimizations to scale interactive visualizations to massive datasets.

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تاریخ انتشار 2014