Making big data, in theory

In this paper, I explore four conceptual interventions that can contribute to the “big theory” sorely needed in regard to big data. This includes temporality and the possibilities of “dated theory,” the implicit histories of the meta- prefix shaping notions of metadata, “the dialectic of surveillance and recognition,” and questions of interpretation understood in terms of “rotted data” and “thick data.” In developing these concepts, I seek to expand frameworks for addressing issues of time, context, and power. It is vital that a vibrant theoretical discussion shape emerging regimes of “big data,” as these regimes are poised to play an important role regarding the mutual constitution of technology and society.