Abstract:
The big data revolution is changing the way data is produced, analyzed, and valued. In the environmental sciences, big data has made it onto the agenda through calls to utilize the current data “deluge” more effectively and a desire for more complete measurement. However, a wider philosophical and ethical critique of big data is needed to assess its utility for environmental explanation. We distil three definitions relevant to the environmental sciences, focusing on the characteristics that make data “big,” the methods of analysis used, and the models of explanation favoured by big data analysts. We critically interrogate the new priorities implicit within big environmental data, and for a historical analogue we compare the big data moment in the environmental sciences to the period in the 1970s when systems theory was being invoked as a paradigmatic shift. Like systems theory, big data is poised to become the new lingua franca of many fields of scientific inquiry. Here we echo Barbara Kennedy's caution that whilst new methods of analysis seem fascinating and promissory, scientists must always be accountable to the “naughty” world in which we live, rather than the clean abstractions that we seek to generate.