This paper reviews the studies about conceptualization, representation of geographic information uncertainty, as well as its influence in decision-making process.
Some typologies are reviewed and the author proposed a more comprehensive one. However, the explanation of each components in the typology is not so clear. For example, when explaining “interrelatedness”, the author uses an example of proving whether a story is authentic. I don’t think it is appropriate, and it makes me confuse this component with “lineage” even I know they are different. Besides, the author mention uncertainty is related to data quality and reliability. He can have more explicit statements to distinguish them, which will make readers more understand uncertainty.
There is an interesting question promoted in the paper. That is whether the representation of uncertainty will create new uncertainty. For me, the answer is yes. Representing uncertainty through some kinds of symbols is exactly a process of abstraction. There will be some information loss and new uncertainty happens. It is worth noting that even previous studies have evaluated some symbol can symbolization of uncertainty can lead to better decision-making. But they didn’t tell the audience the theory behind the use of these symbols. Or there may be no theoretical supports. GIScience involves interdisciplinary studies, the symbols proposed before cannot apply to all situations. How to choose appropriate symbols to represent uncertainty is important. Therefore, we should have theoretical supports for this.
For decision-making, different studies have different conclusions about the helpfulness of including uncertainty. It may or may not lead to better decisions. I will argue that more informed is not necessarily better. Some problems are complex enough, including uncertainty will disturb the judgements of decision-makers. They do not always wish for knowing everything.