Undoing decontextualization or how scientists come to understand their own data/graphs


Correspondence to: Wolff-Michael Roth; e-mail: wolffmichael.roth@gmail.com


The sciences have been so successful in the course of recent human history because the (mathematical) representations they use articulate laws and relations independent of contextual particulars and contingencies of concrete situations. This allows verification anywhere and at any time, and, therefore, the objectivity of scientific phenomena. Decontextualization, however, may make interpretation difficult even for scientists. This ethnographic study of a scientific lab investigating the absorption of light in the eyes of salmonid fish was designed to investigate the role of context in the understanding of data and graphs in science. Drawing on data from a 5-year ethnographic study of laboratory science, I exhibit the effort scientists mobilize to learn by reconstructing the context from which their data have been abstracted. Without recontextualization, scientists struggle making sense of the study results that emerge from their work. Scientists require familiarity with the settings from which the data derive and with the entire transformation process that produce graphical representations to be able to interpret the data. This has considerable implications for teaching graphs and graphing and for using graph interpretation tasks. Rather than being a decontextualized basic process skill, graphing competency is a function of familiarity with both scientific object and the research process as a whole.