Using Gap Charts to Visualize the Temporal Evolution of Ranks and Scores
Résumé
We present Gap Charts, a novel class of line charts designed for visualizing the evolution of rankings over time, with a particular focus on sports data. Gap Charts show entries, e. g., teams participating in a competition, that are ranked over time according to a performance metric like a growing number of points or a score. The main advantages of Gap Charts are that 1) tied entries never overlap—only changes in rank generate limited overlap between time-steps; and 2) gaps between entries show the magnitude of their score difference. We evaluate the effectiveness of Gap Charts for performing different types of tasks, and find that they outperform standard time-dependent ranking visualizations for tasks that involve identifying and understanding evolutions in both ranks and scores. Finally, we show that Gap Charts are a generic and scalable class of line charts by applying them to a variety of different datasets.
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