Taking the visual appeal of the ‘bell curve’ as an example, this paper discusses in how far the availability of quantitative approaches (here: statistics) that comes along with representational standards immediately affects qualitative concepts of scientific reasoning (here: normality). Within the realm of this paper I shall focus on the relationship between normality, as defined by scientific enterprise, and normativity, that result out of the very processes of standardisation itself. Two hypotheses are guiding this analysis: (1) normality, as it is (...) defined by the natural and the life sciences, must be regarded as an ontological, but epistemological important fiction and (2) standardised, canonical visualisations (such as the ‘bell curve’) impact on scientific thinking and reasoning to a significant degree. I restrict my analysis to the epistemological function of scientific representations of data: This means identifying key strategies of producing graphs and images in scientific practice. As a starting point, it is crucial to evaluate to what degree graphs and images could be seen as guiding scientific reasoning itself, for instance in attributing to them a certain epistemological function within a given field of research. (shrink)

After the United States Congress passed the Water Pollution Control Act of 1948, biologists played an increasingly significant role in scientific studies of water pollution. Biologists interacted with other experts, notably engineers, who managed the public agencies devoted to water pollution control. Although biologists were at first marginalized within these agencies, the situation began to change by the early 1960s. Biological data became an integral part of water pollution control. While changing societal values, stimulated by an emerging ecological awareness, may (...) explain broader shifts in expert opinion during the 1960s, this article explores how graphs changed experts’ perceptions of water pollution. Experts communicated with each other via reports, journal articles, and conference speeches. Those sources reveal that biologists began experimenting with new graphical methods to simplify the complex ecological data they collected from the field. Biologists, I argue, followed the engineers’ lead by developing graphical methods that were concise and quantitative. Their need to collaborate with engineers forced them to communicate, negotiate, and overcome conflicts and misunderstandings. By meeting engineers’ expectations and promoting the value of their data through images as much as words, biologists asserted their authority within water pollution control by the early 1960s. (shrink)

While symbolic colour use has always played a conspicuous role in science research and education, the use of colour in historic diagrams remains a lacuna in the history of science. Investigating the colour use in diagrams often means uncovering a whole cosmology that is not otherwise explicit in the diagram itself. The periodic table is a salient and iconic example of non-mimetic colour use in science. Andreas von Antropoff's (1924) rectangular table of recurrent rainbow colours is famous, as are Alcindo (...) Flores Cabral's (1949) application of colour in his round snail form, using the RGB scheme, and Mazurs's (1967) pine tree system, consisting of warm and cold colours that he attributed to specific groups of elements—an attribution that we can relate back to humoralism and alchemy. From the first periodic tables in the 19th century, individual researchers have used different colour regimes. While standardization may play an obvious role in chemistry and its diagrams, all the more impressive is the anarchistic use of colour in the various diagrams which continue to be created. This article focuses on periodic tables in chemical journals and text books, and explores and compares the development of colour codes found in the few existing polychrome diagrams from the 1920s to the 1970s. (shrink)

The purpose of this study is to examine how trends in the use of images in modern life science journals have changed since the spread of computer-based visual and imaging technology. To this end, a new classification system was constructed to analyze how the graphics of a scientific journal have changed over the years. The focus was on one international peer-reviewed journal in life sciences, Cell, which was founded in 1974, whereby 1725 figures and 160 tables from the research articles (...) in Cell were sampled. The unit of classification was defined as a graphic and the figures and tables were divided into 5952 graphics. These graphics were further classified into hierarchical categories, and the data in each category were aggregated every five years. The following categories were observed: data graphics, explanation graphics, and hybrid graphics. Data graphics increased by more than sixfold between 1974 and 2014, and some types of data graphics including mechanical reproduction images and bar charts displayed notable changes. The representation of explanatory graphics changed from hand-painted illustrations to diagrams of Bezier-curves. It is suggested that in addition to the development of experimental technologies such as fluorescent microscopy and big data analysis, continuously evolving application software for image creation and researchers’ motivation to convince reviewers and editors have influenced these changes. (shrink)