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 (...) the parts and operations work together to produce the phenomenon and what experiments need to be done to improve on the existing account. We examine how these functions are served by diagrams in circadian rhythm research. (shrink)

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.

: 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 (...) his strategy of moving—via conjectural visual models—between the phenomenology of particulars (often displayed as patterns) and the general features of dynamical phenomena which he depicted as structures. (shrink)

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, (...) such as the influence of bias and prejudice. The scheme of inferential calculations invokes a Peircian concept of ‘belief’ as the propensity to choose a particular course of action. (shrink)

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.

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 (...) contexts of practice. However, the existence of common strategies shows that this diversity masks an important repertoire of cognitive strategies. Scientists use this repertoire to adapt their representations to meet the cognitive demands of different contexts of practice. This paper considers the implications of this finding for the notion of scientists as cognitive agents in distributed knowledge-producing systems. (shrink)