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Socialising 'Big Data'


With the turn to ‘big data’ analytics in business, government and academia, complex issues of behaviour change, risk management and harm prevention are framed in terms of data collection, mining, aggregation, visualisation and synthesis.

Through these and other methods, data-objects of various kinds are generated to exploit the hidden potentials and knowledge in big data to tell us more about the risks and vulnerabilities of people and things. However, at the same time these data-objects themselves introduce new risks such as privacy, security, relevance, accuracy, representativeness and stability and make ways of knowing vulnerable to various forms of failure.

The challenge of big data is not that it is big, but that it creates new vulnerabilities in part because of the tendency to overlook the social lives of data-objects, which are neither natural nor technical phenomena, but enacted and sustained through multiple and selective social practices, and hence always and already limited and limiting. We seek to develop a ‘social literacy’ about big data rather than reiterating the urgent need to respond to ‘the data deluge,’ and to locate the successes and failures of the turn to data in ways that link them to practices and specific situations.


Dr Evelyn Ruppert, OU, Centre for Research on Socio-Cultural Change (CRESC)
Professor Penny Harvey and Dr Hannah Knox, Manchester, CRESC
Dr Adrian Mackenzie and Dr Ruth McNally, Centre for Economic and Social Aspects of Genomics (Cesagen), Lancaster
Professor Celia Lury, Centre for Interdisciplinary Methodologies (Warwick).