  We present ReViVD, a tool for exploring and filtering large trajectory-based
datasets using virtual reality. ReViVD's novelty lies in using simple 3D shapes
-- such as cuboids, spheres and cylinders -- as queries for users to select and
filter groups of trajectories. Building on this simple paradigm, more complex
queries can be created by combining previously made selection groups through a
system of user-created Boolean operations. We demonstrate the use of ReViVD in
different application domains, from GPS position tracking to simulated data
(e.g., turbulent particle flows and traffic simulation). Our results show the
ease of use and expressiveness of the 3D geometric shapes in a broad range of
exploratory tasks. ReViVD was found to be particularly useful for progressively
refining selections to isolate outlying behaviors. It also acts as a powerful
communication tool for conveying the structure of normally abstract datasets to
an audience.
