This paper discusses the ways in which uncertainty may best be quantified and then presented to decision-makers. As shown in one of the exercises in the paper with students tasked with choosing the new location of certain parks and airports, the ones that were exposed to the best uncertainty visualization methods typically made the best informed decision. McEachron presents a data matrix of which various different forms of uncertainty are presented, which range on the the precision of the data, to the completeness of the method. The study of uncertainty seems to rely entirely on academic honesty, and represents in very clear ways what’s missing from the study. The issues with this kind of study emerge when communication between academia and decision-makers take place. Often times, uncertainty can be mistaken for a case of faulty data, and if this is not presented adequately, can lead to a severe miscommunication.
A major problem that McEachron identifies is how to represent the varying different forms of uncertainty. The topic of geovisualization came to mind. Since geovisualization is concerned with the exploration and manipulation of data, perhaps it’s through this particular lens in which we can apply the multitudes of uncertainty dimensions to a geographic sense. As with many challenges which come with having non-academics engaging with this data, proper interfaces need to be established. Both on a technological sense and a human sense. So while issues with quantifying uncertainty remain at the forefront of this particular paper, I sense that these may have implications in the way uncertainty is subjectively perceived.