Data-driven sciences: From wonder cabinets to electronic databases #bigdata

“Even by the journal’s own standards, this was a wild claim. In July 2008, Wired magazine announced on its cover nothing less than “The End of Science”. It explained that “The quest for knowledge used to begin with grand theories. Now it begins with massive amounts of data”.¹ Such claims about the emergence of a new “data-driven” science in response to a “data deluge” have now become common, from the pages of The Economist to those of Nature.² Proponents of “data-driven” and “hypothesis-driven” science argue over the best methods to turn massive amounts of data into knowledge. Instead of jumping into the fray, I would like to historicize some of the questions and problems raised by data-driven science, taking as a point of departure the three rich papers by Isabelle Charmantier and Staffan Müller-Wille on Linnaeus’ information processing strategies, Sabina Leonelli and Rachel Ankeny on model organisms databases, and Peter Keating and Alberto Cambrosio on microarray data in clinical research”