Data is an essential part of culture, culture cultivates data and uses this data to inscribe meaning. Again I use the word meaning as I did in my last blog but it is intrinsic to understanding culture. The term Data Friction can be the processes that can make obtaining and culminating data difficult. Paul Edwards uses the example of scientists using global temperatures to track climate change. The difficulties they have faced has been the fact that there is not one standard for this collection of data, they would have to assimilate data from different metrics, different methods, or change platforms in which the data was collected. Climate change experts have been discredited by skeptics because of the nature of data friction, their argument being that they cant possibly conclude conclusive data as the methods around the would conflict.
This example calls for a standardization of data collection around the world, a change in the scientific culture that could lead to a better understanding of data itself and therefore science but that also effects the wider culture outside of the science world as the general public’s knowledge of climate is effected and can change publics behaviour.
Edwards, Paul N. (2010) ‘Introduction’ in A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming Cambridge, MA: MIT Press: xiii-xvii