Interactive Exploration of Large Quantity of Multidimensional Data
Christophe Hurter (DTI R&D)

Abstract:

When displaying thousands of aircraft trajectories on a screen, the visualization is spoiled by a tangle of trails. The visual analysis is therefore difficult, especially if a specific class of trajectories in an erroneous dataset has to be studied. We designed two 3D interaction techniques to dig into multidimensional datasets: FromDaDy and Moleview. FromDaDy is a trajectory visualization tool that tackles the difficulties of exploring the visualization of multiple trails. This multidimensional data exploration is based on scatterplots, brushing, pick and drop, juxtaposed views and rapid visual design. Through two real-world scenarios, we show how FromDaDy supports iterative queries and the extraction of trajectories in a dataset that contains up to 5 million datapoints. Moleview is a new type of semantic lens which selects a specific spatial and attribute-related data range. The lens keeps the selected data in focus unchanged and continuously deforms the data out of the selection range in order to maintain the context around the focus. Moleview is simple to implement and provides real-time performance on large datasets. We demonstrate Moleview with data from air and road traffic control, medical imaging, and software comprehension applications.