Tabula in action: a sampling middleware for interactive geospatial visualization dashboards

In this paper, we demonstrate Tabula, a middleware that sits between the data system and the geospatial visualization dashboard to increase user interactivity. The proposed system adopts a sampling cube approach that stores prematerialized spatial samples and allows data scientists to define their own accuracy loss function such that the produced samples can be used for various user-defined visualization tasks. The system ensures that the difference between the sample fed into the dashboard and the raw query answer never exceeds the user-specified loss threshold. For demonstration purposes, we connect Apache Zeppelin, a visualization dashboard, to the system and show how Tabula accelerates interactive visualizations on NYC Taxi Trip data, Yelp review data and San Diego Smart Streetlights data.