Visual Data – Reasons to Be Relied on?

In Nicola Mößner & Alfred Nordmann (eds.), Reasoning in Measurement. New York: Routledge. pp. 99-110 (2016)
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Abstract

In today’s science, the output of measurement processes are often visual representations of the data detected. Moreover, we find such visual data as parts of scientific reasoning in different contexts. In this article, we will take a look at two of them. On the one hand, visual representations are used as a kind of surrogate for the real object to ask questions about it – we will call this the exploratory use of visual data. On the other hand, visualisations are often used to communicate research results to scientific peers or to laymen. Instances of the latter case we will subsequently call the explanatory use of visual data. However, in both contexts the question arises what might justify these epistemic practices. Believing without reasons is epistemically irresponsible, it leads to gullibility. Thus, we will try to answer the question whether there are any reasons to support our epistemic practices concerning scientific visualisations in the above-mentioned senses and whether these are good reasons to rely on.

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Nicola Mößner
Aachen University of Technology

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