Dataopsy: Scalable and Fluid Visual Exploration using Aggregate Query
  Sculpting
Md Naimul Hoque Niklas Elmqvist
We present aggregate query sculpting (AQS), a faceted visual query technique
for large-scale multidimensional data. As a "born scalable" query technique,
AQS starts visualization with a single visual mark representing an aggregation
of the entire dataset. The user can then progressively explore the dataset
through a sequence of operations abbreviated as P6: pivot (facet an aggregate
based on an attribute), partition (lay out a facet in space), peek (see inside
a subset using an aggregate visual representation), pile (merge two or more
subsets), project (extracting a subset into a new substrate), and prune
(discard an aggregate not currently of interest). We validate AQS with
Dataopsy, a prototype implementation of AQS that has been designed for fluid
interaction on desktop and touch-based mobile devices. We demonstrate AQS and
Dataopsy using two case studies and three application examples.