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 FromDaDy, 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. Users can organize the workspace composed of multiple juxtaposed views. They can define the visual configuration of the views by connecting data dimensions from the dataset to Bertin's visual variables. They can then brush trajectories, and with a pick and drop operation they can spread the brushed information across views. They can then repeat these interactions, until they extract a set of relevant data, thus formulating complex queries. 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 data.
McGuffin and Balakrishnan (M&B) have recently reported evidence that target expansion during a reaching movement reduces pointing time even if the expansion occurs as late as in the last 10% of the distance to be covered by the cursor. While M&B massed their static and expanding targets in separate blocks of trials, thus making expansion predictable for participants, we replicated their experiment with one new condition in which the target could unpredictably expand, shrink, or stay unchanged. Our results show that target expansion occurring as late as in M&B's experiment enhances pointing performance in the absence of expectation. We discuss these findings in terms of the basic human processes that underlie target-acquisition movements, and we address the implications for user interface design by introducing a revised design for the Mac OS X Dock.
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