Probing Projections: Interaction Techniques for Interpreting Arrangements and Errors of Dimensionality Reductions
Probing Projections: Interaction Techniques for Interpreting Arrangements and Errors of Dimensionality Reductions
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DOI：
10.1109/tvcg.2015.2467717
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发表时间：
2016-01-01
影响因子：
5.2
通讯作者：
Thom, Andreas
中科院分区：
文献类型：
--
作者：
Stahnke, Julian;Doerk, Marian;Thom, Andreas
我们引入了一套集成的交互技术来解释和询问降维数据。投影技术通常旨在使高维信息空间以平面布局的形式可见。然而，由此产生的数据预测的含义可能很难理解。为什么元素被放置得很远或很近，以及任何投影技术不可避免的近似误差没有暴露给观众，这一点很少清楚。以往的降维研究主要集中在数据预测的有效生成上。模型的交互式定制，以及不同投影技术的比较。对于数据投影产生的可视化如何进行交互的研究很少。我们贡献的概念探测作为一个综合的方法来解释的意义和质量的可视化，并提出了一套互动的方法来检查降维数据以及投影本身。这些方法可以让查看者看到近似误差。询问元素的位置，将它们相互比较，并可视化数据维度对投影空间的影响。我们创建了一个基于Web的系统，实现这些方法，并报告使用原型检查多维数据集的数据分析师的评估结果。
We introduce a set of integrated interaction techniques to interpret and interrogate dimensionality-reduced data. Projection techniques generally aim to make a high-dimensional information space visible in form of a planar layout. However, the meaning of the resulting data projections can be hard to grasp. It is seldom clear why elements are placed far apart or close together and the inevitable approximation errors of any projection technique are not exposed to the viewer. Previous research on dimensionality reduction focuses on the efficient generation of data projections. interactive customisation of the model, and comparison of different projection techniques. There has been only little research on how the visualization resulting from data projection is interacted with. We contribute the concept of probing as an integrated approach to interpreting the meaning and quality of visualizations and propose a set of interactive methods to examine dimensionality-reduced data as well as the projection itself. The methods let viewers see approximation errors. question the positioning of elements, compare them to each other, and visualize the influence of data dimensions on the projection space. We created a web-based system implementing these methods, and report on findings from an evaluation with data analysts using the prototype to examine multidimensional datasets.