Uncertainty lies at the core of GISci where MacEachren et al. acknowledges the GISci community has given more attention to formalizing approaches to uncertainty than in other communities such as information visualization communities (p. 144). The authors go through several examples of how uncertainty can be visualized from changes in hue to symbols with different transparencies to depict where uncertain data may exist. What peaked my interest was the interactive visualization techniques that users can control depictions of uncertainty. Instead of permanently adding a layer of complexity that can obstruct and confuse the readers from what the data is trying to depict, the user is in full control of how much or little information (with regards to uncertainty) is available to them. To me this seems like a better solution than to simply find a single “ideal” ways to represent uncertainty visually in a static manner – especially since every individual will have their own preferences on what they think “best” means (context matters!). What I don’t quite agree with is the authors’ assertion that humans are not adept to using statistical information to make decisions and base on heuristics (based on a study in 1974). Since the quantitative revolution, hasn’t statistics been bought to the forefront of geography such that we may rely on statistics too much at this point? That being said, visualizing uncertainty can take on many forms, from charts, changes in opacity, 3D graphics where the way in which uncertainty should be viewed will ultimately be context specific to meet the goals of the researcher.


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