Big Data and the Data Revolution have been pitched as a potential transformation of all modes of digital data collection, organization, storage, mining, analytics and visualization. The proliferation of digital infrastructures and information after the social media revolution called Web 2.0, has led to a global movement around leveraging the enormous potential of data to drive decision-making. The move for more data-driven knowledge production is also marked by the emergence of a new, highly sought after academic discipline called Data Science, which is essentially a hybrid of computer science and statistics. The new episteme of data-driven knowledge production is primarily rooted in a meshed network of concepts from statistics, cybernetics, micro to planetary scale computing and information flows, statecraft and governmentality, standardisation and classification, and so on. Not surprisingly then, social data – the data collected and generated by governments, academia, businesses including technology companies, and civil society organisations pertaining to education, health, development, poverty, public behaviour, etc. – has been a key site for the constitution and circulation of the new episteme of data-drivenness. Taking this as a point of departure, the project explored the historical and emergent conditions of data-driven – statistical and computational – knowledge production in the social sector. The research focus included history of statistics, evolution of survey and social data collection systems, and the Big Data emergences in the Indian context.
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