Small Multiples, Large Singles: A New Approach for Visual Data Exploration
Small Multiples, Large Singles: A New Approach for Visual Data Exploration
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DOI：
10.1111/cgf.12106
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发表时间：
2013-06-01
影响因子：
2.5
通讯作者：
van Wijk, Jarke J.
中科院分区：
文献类型：
--
作者：
van den Elzen, Stef;van Wijk, Jarke J.
我们提出了一种新的可视化勘探方法的基础上，有效和高效的数据分析小多次和大单。用户可以通过提供当前状态的多个备选方案来探索状态空间。然后，用户可以选择备选方案并继续分析。此外，探索过程中的中间步骤被保留，并且可以使用基于众所周知的撤消-重做堆栈和幻灯片隐喻的直观导航机制来重新访问和调整。作为概念证明，探索方法在原型中实现。探索方法的有效性进行了测试，使用正式的用户研究比较四种不同的交互方法。通过使用Small Multiples作为数据探索方法，用户在回答问题时需要更少的步骤，并且还可以在相同的时间内探索状态空间的更大部分，为他们提供更广泛的数据视角，从而降低错过重要特征的机会。此外，用户更喜欢使用小倍数而不是非小倍数变量的视觉探索。
We present a novel visual exploration method based on small multiples and large singles for effective and efficient data analysis. Users are enabled to explore the state space by offering multiple alternatives from the current state. Users can then select the alternative of choice and continue the analysis. Furthermore, the intermediate steps in the exploration process are preserved and can be revisited and adapted using an intuitive navigation mechanism based on the well-known undo-redo stack and filmstrip metaphor. As proof of concept the exploration method is implemented in a prototype. The effectiveness of the exploration method is tested using a formal user study comparing four different interaction methods. By using Small Multiples as data exploration method users need fewer steps in answering questions and also explore a significantly larger part of the state space in the same amount of time, providing them with a broader perspective on the data, hence lowering the chance of missing important features. Also, users prefer visual exploration with small multiples over non-small multiple variants.