Minds and Machines 29 (1):87-107 (2018)

Authors
Michael T. Stuart
University of Geneva
Nancy Nersessian
Harvard University
Abstract
Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The visualization is unusual in that it depicts the dynamics and structure of a computer model instead of that model’s target system, and because it is generated algorithmically. Using considerations from epistemology and aesthetics, we explore how this new kind of visualization increases scientific understanding of the content and function of computer models in systems biology to reduce epistemic opacity.
Keywords Computer Simulation  Scientific Understanding  Scientific Visualization  imagination  epistemic opacity
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Reprint years 2018, 2019
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DOI 10.1007/s11023-018-9484-3
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References found in this work BETA

Understanding Why.Alison Hills - 2015 - Noûs 49 (2):661-688.
No Understanding Without Explanation.Michael Strevens - 2013 - Studies in History and Philosophy of Science Part A 44 (3):510-515.
Understanding Why.Alison Hills - 2016 - Noûs 50 (4):661-688.
True Enough.Catherine Z. Elgin - 2004 - Philosophical Issues 14 (1):113–131.

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