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  1. Visual cognition: Where cognition and culture meet.David C. Gooding - 2006 - Philosophy of Science 73 (5):688-698.
    Case studies of diverse scientific fields show how scientists use a range of resources to generate new interpretative models and to establish their plausibility as explanations of a domain. They accomplish this by manipulating imagistic representations in particular ways. I show that scientists in different domains use the same basic transformations. Common features of these transformations indicate that general cognitive strategies of interpretation, simplification, elaboration, and argumentation are at work. Social and historical studies of science emphasize the diversity of local (...)
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  • Visualizing Scientific Inference.David C. Gooding - 2010 - Topics in Cognitive Science 2 (1):15-35.
    The sciences use a wide range of visual devices, practices, and imaging technologies. This diversity points to an important repertoire of visual methods that scientists use to adapt representations to meet the varied demands that their work places on cognitive processes. This paper identifies key features of the use of visualization in a range of scientific domains and considers the implications of this repertoire for understanding scientists as cognitive agents.
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  • Simulation Methods for an Abductive System in Science.D. C. Gooding & T. R. Addis - 2008 - Foundations of Science 13 (1):37-52.
    Syntactic and structural models specify relationships between their constituents but cannot show what outcomes their interaction would produce over time in the world. Simulation consists in iterating the states of a model, so as to produce behaviour over a period of simulated time. Iteration enables us to trace the implications and outcomes of inference rules and other assumptions implemented in the models that make up a theory. We apply this method to experiments which we treat as models of the particular (...)
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  • From phenomenology to field theory: Faraday's visual reasoning.David C. Gooding - 2006 - Perspectives on Science 14 (1):40-65.
    : Faraday is often described as an experimentalist, but his work is a dialectical interplay of concrete objects, visual images, abstract, theoretically-informed visual models and metaphysical precepts. From phenomena described in terms of patterns formed by lines of force he created a general explanation of space-filling systems of force which obey both empirical laws and principles of conservation and economy. I argue that Faraday's articulation of situated experience via visual models into a theory capable of verbal expression owed much to (...)
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  • Rethinking correspondence: how the process of constructing models leads to discoveries and transfer in the bioengineering sciences.Nancy J. Nersessian & Sanjay Chandrasekharan - 2017 - Synthese 198 (Suppl 21):1-30.
    Building computational models of engineered exemplars, or prototypes, is a common practice in the bioengineering sciences. Computational models in this domain are often built in a patchwork fashion, drawing on data and bits of theory from many different domains, and in tandem with actual physical models, as the key objective is to engineer these prototypes of natural phenomena. Interestingly, such patchy model building, often combined with visualizations, whose format is open to a wide range of choice, leads to the discovery (...)
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  • Simulation Methods for an Abductive System in Science.T. R. Addis & D. C. Gooding - 2008 - Foundations of Science 13 (1):37-52.
    We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, (...)
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  • Diagrams as Tools for Scientific Reasoning.Adele Abrahamsen & William Bechtel - 2015 - Review of Philosophy and Psychology 6 (1):117-131.
    We contend that diagrams are tools not only for communication but also for supporting the reasoning of biologists. In the mechanistic research that is characteristic of biology, diagrams delineate the phenomenon to be explained, display explanatory relations, and show the organized parts and operations of the mechanism proposed as responsible for the phenomenon. Both phenomenon diagrams and explanatory relations diagrams, employing graphs or other formats, facilitate applying visual processing to the detection of relevant patterns. Mechanism diagrams guide reasoning about how (...)
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  • Drawing in a Social Science: Lithic Illustration.Dominic McIver Lopes - 2009 - Perspectives on Science 17 (1):pp. 5-25.
    Scientific images represent types or particulars. According to a standard history and epistemology of scientific images, drawings are fit to represent types and machine-made images are fit to represent particulars. The fact that archaeologists use drawings of particulars challenges this standard history and epistemology. It also suggests an account of the epistemic quality of archaeological drawings. This account stresses how images integrate non-conceptual and interepretive content.
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