From self-tracking to smart urban infrastructures: towards an interdisciplinary research agenda on Big Data

Abstract

Recent debates on surveillance have emphasised the now myriad possibilities of automated, software-based data gathering, management and analysis. One of the many terms used to describe this phenomenon is ‘Big Data’. The field of Big Data covers a large and complex range of practices and technologies from smart borders to CCTV video analysis, and from consumer profiling to self-tracking applications. The paper’s aim is to explore the surveillance dynamics inherent in contemporary Big Data trends. To this end, the paper adopts two main perspectives concerned with two complementary expressions of Big Data: (1) the individual use of various techniques of self-surveillance and tracking and (2) the simultaneous trend to optimise urban infrastructures through smart information technologies. Drawing upon exploratory research conducted by the authors, the paper shows that both expressions of Big Data present a range of common surveillance dynamics on at least four levels: agency, temporality, spatiality and normativity. On these grounds, the paper highlights a series of important issues to explore in future research.