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Scientific Visualisation

Epistemic Weight and Surpluses

Marianne Richter

Much of the recent confidence in the future of science and technology stems from advances in scientific visualisation. But is it right to assume that visual – and especially pictorial – measures carry special epistemic weight in the context of scientific reasoning? Do pictorial approaches have any surpluses, compared to other semiotic types? This book delves into these issues from the point of view of the philosophy of science. New examples from the field of scientific visualisation are introduced in order to account for the epistemic weight and surpluses of syntactically dense – pictorial – symbol systems.
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I Introduction


← 18 | 19 → All sciences must deal with the problem of selecting and constituting “working objects”

Daston & Galison (2007), p. 19

Despite their prevalence, visual – and especially picture-like or pictorial – measures have been afforded only sparse attention in the philosophy of science. This is perplexing as practice indicates that the ever-present ‘scientific figures’ (abbreviated ‘Fig.’) are conceived of as ingredients of both pictorial and argumentative systems. Fig. 1, for instance, exemplifies a strategy of visualisation that is meant to render the numerical solution of simulations comparable to the outcomes of confocal laser scanning microscopy. More precisely, Fig. 1 adopts the associated optical effects as displayed by the targeted micrographs (cf. Fig. 2), such as the afterglow of the stimulated fluorescent markers and the stark contrast between the glowing and the darker areas. Hence, the numerical solutions of the simulation – which could actually be presented much more articulately, considering the source matrices on which they are based – are rendered indistinct, up to a degree where it becomes difficult to distinguish between all the distinct values that are used to represent foreground and background, cell tissue and plasma, etc. Still, on account of these very figures, it is argued that there are differences between the diffusion of signalling molecules and their transport via motor proteins, such as crowding behaviour in the case of transport (Fig. 1 [right]; cf. Falk et al. 2009, p. 173). It thus seems, after all, that these figures are truly used to provide support...

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