Data set used in the paper

Visual Analytics Methodology for Eye Movement Studies
by Gennady Andrienko, Natalia Andrienko, Michael Burch, Daniel Weiskopf
IEEE Transactions on Visualization and Computer Graphics
(Proceedings IEEE VAST 2012),
vol. 18(12), pp.2889-2898, Dec. 2012

The eye movement data were acquired in a controlled laboratory experiment previously conducted by Burch et al. The task for this experiment was to find the least common ancestor for a set of marked leaf nodes in node-link tree diagrams. Tree layout, tree orientation, and number of marked leaf nodes were chosen as independent variables and task completion time and accuracy were recorded as dependent variables. This study emphasized high accuracy, i.e., participants were instructed to answer as correctly as possible, resulting in an overall accuracy of more than 97 percent. By focusing on a high degree of accuracy, participants had to apply some kind of reliable visual task solution strategy to come up with correct answers.

The study was based on a repeated-measures design in within-subjects style. A Tobii T60 XL eye tracking system was used to record eye movement data, i.e., fixation durations and saccades, along with completion times and accuracies. Participants sat in front of a TFT screen at a resolution of 1920x1200 pixels at a distance given by the calibration feature of the eye tracking system. A minimum of 10 pixels covering and 30 ms fixation duration were chosen as key parameters, i.e., if a personís gaze stayed for at least 30 ms in the same region of 10 pixels width and height, this was registered as an eye fixation. The 38 participants came from Western countries, with a preference for left-to-right reading direction.

In the experiment, participants were shown tree data stimuli in three different node-link layouts: traditional, orthogonal, and radial. The non-radial diagrams had four different root orientations (top, right, bottom, left). Furthermore, the number of marked leaf nodes varied between three, six, and nine. There were three blocks each containing stimuli with the same layout. Inside each block, the stimuli were randomized. The stimuli data was generated by a stochastic algorithm before running the study. The test system displayed the next stimulus when the participant confirmed to proceed (continue-on-demand). In total, there were 2,052 individual tests.

The task for the participants was to locate the least common ancestor of a set of red colored leaf nodes. Once the location of the correct node was found, the participant had to confirm it by a mouse click. This task was chosen because the hierarchy had to be understood and a strategy had to be applied to answer correctly. The differences between the tree layouts, orientations, and number of marked leaf nodes might cause different task solution strategies. The applied strategies were of special interest for the researchers.

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