Visualizations of hierarchical data can often be explored interactively. For example, in geographic visualization, there are continents, which can be subdivided into countries, states, counties and cities. Similarly, in models of viruses or bacteria at the highest level are the compartments, and below that are macromolecules, secondary structures (such as α‐helices), amino‐acids, and on the finest level atoms. Distinguishing between items can be assisted through the use of color at all levels. However, currently, there are no hierarchical and adaptive color mapping techniques for very large multi‐scale visualizations that can be explored interactively. We present a novel, multi‐scale, color‐mapping technique for adaptively adjusting the color scheme to the current view and scale. Color is treated as a resource and is smoothly redistributed. The distribution adjusts to the scale of the currently observed detail and maximizes the color range utilization given current viewing requirements. Thus, we ensure that the user is able to distinguish items on any level, even if the color is not constant for a particular feature. The coloring technique is demonstrated for a political map and a mesoscale structural model of HIV. The technique has been tested by users with expertise in structural biology and was overall well received.

中文翻译：

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Cuttlefish：动态多尺度可视化的颜色映射

分层数据的可视化通常可以交互地探索。例如，在地理可视化中，有大陆，可以细分为国家、州、县和城市。同样，在病毒或细菌模型中，最高层是区室，下面是大分子、二级结构（如 α 螺旋）、氨基酸，最细层是原子。通过在各个级别使用颜色可以帮助区分物品。然而，目前还没有用于可以交互式探索的超大型多尺度可视化的分层和自适应颜色映射技术。我们提出了一种新颖的多尺度颜色映射技术，用于根据当前视图和比例自适应调整颜色方案。颜色被视为一种资源并顺利地重新分配。该分布会根据当前观察到的细节的比例进行调整，并根据当前的观看要求最大化颜色范围的利用率。因此，我们确保用户能够在任何级别上区分项目，即使特定功能的颜色不是恒定的。针对政治地图和艾滋病毒的中尺度结构模型演示了着色技术。该技术已经过具有结构生物学专业知识的用户的测试，总体上受到好评。