Why are graphs so central in science?

Biology and Philosophy 6 (2):181-203 (1991)
This paper raises the question of the prominence and use of statistical graphs in science, and argues that their use in problem solving analysis can best be understood in an ‘interactionist’ frame of analysis, including bio-emotion, culture, social organization, and environment as elements. The frame contrasts both with philosophical realism and with social constructivism, which posit two variables and one way causal flows. We next posit basic differences between visual, verbal, and numerical media of perception and communication. Graphs are thus seen as key interactive sites where different media are transformed into more interpretable forms. Examples are taken from Limnology where numbers are transformed into graphs to find patterns in them, and thus, by implication in the environmental materials from which the numerical measurements were taken. Their revisualization by passes a human cognitive limitation, for the direct analysis — interpretation of lists and tables of numbers, visual imaging being a cognitive strength. Sense of problem, conceptual repertoire, and social relations are seen to direct this pattern search and interpretive process.
Keywords Interactive mechanisms  research practice  statistical graphs  visuals
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DOI 10.1007/BF02426837
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References found in this work BETA
Bruno Latour & Steve Woolgar (1982). Laboratory Life. The Social Construction of Scientific Facts. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 13 (1):166-170.

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