Procedural annotation of uncertain information

In many applications of scientific visualization, a large quantity of data is being processed and displayed in order to enable a viewer to make informed and effective decisions. Since little data is perfect, there is almost always some degree of associated uncertainty. This uncertainty is an important part of the data and should be taken into consideration when interpreting the data. Uncertainty, however, should not overshadow the data values. Many methods that address the problem of visualizing data with uncertainty can distort the data and emphasize areas with uncertain values. We have developed a method for showing the uncertainty information together with data with minimal distraction. This method uses procedurally generated annotations which are deformed according to the uncertainty information. As another possible technique we propose distorting glyphs according to the uncertainty information.