Nathan Yau from FlowingData found a great paper in Nature discussing the importance and problems of visualizing uncertainty from various datasats. Focusing most heavily on genomic data, his results are applicable to a wide variety of datatypes.
Statistical uncertainty weighs heavily on visualization. Every data point has uncertainty associated with it, Krzywinski says. Adding those statistical data to visualizations can quickly overload them. Despite the potential pitfalls of including uncertainty, the visual cues can remind scientists of their data’s ambiguity.
If you’re into biomedical or genomics visualization, you should read the article for information on Harvard Medical’s Caleydo tool.
via Data visualization: ambiguity as a fellow traveler : Nature Methods : Nature Publishing Group.
