Big Data Economies and Ecologies

Big Data generated by digital activities, mobile phone use, transactions, crowdsourcing, digitisation and so on along with innovative modes of analysis such as data linking, mining, correlating, and visualising are reconfiguring social science methods and knowledge practices. Rather than only generating data, social scientists now also scrape, harvest, assemble and re-purpose data generated by numerous digital devices often not of their making. Yet social scientists have long re-used data such as that compiled in documentary archives or generated by censuses and surveys. At issue then is not so much the re-purposing of data but the epistemological and ontological effects of knowledge practices that these new forms of data are mobilising. I examine these effects by thinking about the shifting relations, relays, dependencies and investments between subjects, owners, mediators, translators and gatekeepers that make up the economies and ecologies of Big Data. However, because these complex relations increasingly bury or make the provenance of data inaccessible, I bring attention to how we might think about what methods enact and the kinds of realities that they elevate. I call this ‘decisive data’, a move that understands that the 'reality' of Big Data is to be found in its mobilising effects, that is, worlds that it comes to actualise and legitimise when taken up by methods. It is an approach that doesn’t get further away from but closer to Big Data, not an anti-empiricism but a renewed empiricism that does not stand back and critique facts but gets closer to them as matters of concern. I argue that one ethical challenge is to find ways of being accountable, answerable and responsible to the effects of our methods that mobilise Big Data and the worlds and ways of being they elevate and promote