Peeking Inside the Black Box: A New Kind of Scientific Visualization

Michael T. Stuart*, Nancy J. Nersessian

*此作品的通信作者

研究成果: Article同行評審

5 引文 斯高帕斯(Scopus)

摘要

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 (observed in a qualitative study of a systems biology laboratory) 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.

原文English
頁(從 - 到)87-107
頁數21
期刊Minds and Machines
29
發行號1
DOIs
出版狀態Published - 15 3月 2019

指紋

深入研究「Peeking Inside the Black Box: A New Kind of Scientific Visualization」主題。共同形成了獨特的指紋。

引用此