Graphs effectively communicate data because they capitalize on the visual system's ability to rapidly extract patterns. Yet, this pattern extraction does not occur in a single glance. Instead, research on visual attention suggests that the visual system iteratively applies a sequence of filtering operations on an image, extracting patterns from subsets of visual information over time, while selectively inhibiting other information at each of these moments. To demonstrate that this powerful series of filtering operations also occurs during the perception of visualized data, we designed a task where participants made judgments from one class of marks on a scatterplot, presumably incentivizing them to relatively ignore other classes of marks. Participants consistently missed a conspicuous dinosaur in the ignored collection of marks (93% for a 1s presentation, and 61% for 2.5s), but not in a control condition where the incentive to ignore that collection was removed (25% for a 1s presentation, and 11% for 2.5s), revealing that data visualizations are not "seen" in a single glance, and instead require an active process of exploration.
翻译:图形通过利用视觉系统快速提取图案的能力有效地传递数据。 然而, 这种模式提取并非一目了然。 相反, 视觉关注研究表明, 视觉系统在图像上迭接地应用一系列过滤操作, 随着时间的推移从视觉信息的子集中提取图案, 同时有选择地在每一时刻抑制其他信息。 为了证明这一系列强大的过滤操作也在视觉化数据感知期间发生, 我们设计了一个任务, 让参与者从撒布图上的某一类标记中做出判断, 可能激励他们相对忽略其他标记类别。 参与者总是在忽略的标记收集中遗漏了显著的恐龙( 93% 用于 1 演示, 61% 用于 2.5 ), 但不是在一个控制状态下, 忽略收集的动机被删除了 ( 25% 用于 1 演示, 11% 2.5 ), 显示数据可视化不是一眼就能“ 看见的 ”, 而是需要一个积极的探索过程 。