Parallel coordinates plots (PCPs) are a widely used visualization method, particularly for exploratory analysis. Previous studies show that PCPs perform much more poorly for estimating positive correlation than for estimating negative correlation, but it is not clear if this is affected by the aspect ratio (AR) of the axes pairs. In this paper, we present the results from an evaluation of the effect of the aspect ratio of axes in static (non-interactive) PCPs for two tasks: a) linear correlation estimation and b) value tracing. For both tasks we find strong evidence that AR influences accuracy, including ARs greater than 1:1 being much more performant for estimation of positive correlations. We provide a set of recommendations for visualization designers using PCPs for correlation or value-tracing tasks, based on the data characteristics and expected use cases.

翻译：平行坐标图（PCPs）是一种广泛使用的可视化方法，尤其适用于探索性分析。先前研究表明，在估计正相关性时，平行坐标图的表现远逊于估计负相关性，但尚不清楚这是否受到坐标轴对纵横比（AR）的影响。本文评估了静态（非交互式）平行坐标图中坐标轴纵横比对两项任务的影响结果：a) 线性相关性估计；b) 数值追踪。针对这两项任务，我们均发现有力证据表明纵横比会影响准确性，其中大于1:1的纵横比在正相关性估计中表现显著更优。基于数据特征与预期使用场景，我们为使用平行坐标图进行相关性或数值追踪任务的可视化设计者提供了一系列建议。