In light of recent technological innovations and discourses around data and algorithmic analytics, scholars of many stripes are attempting to develop critical agendas and responses to these developments. In this mutual interview, three scholars discuss the stakes, ideas, responsibilities, and possibilities of critical data studies. The resulting dialog seeks to explore what kinds of critical approaches to these topics, in theory and practice, could open and make available such approaches to a broader audience.

Data analytics, particularly the current rhetoric around “Big Data”, tend to be presented as new and innovative, emerging ahistorically to revolutionize modern life. In this article, we situate one branch of Big Data analytics, spatial Big Data, through a historical predecessor, geodemographic analysis, to help develop a critical approach to current data analytics. Spatial Big Data promises an epistemic break in marketing, a leap from targeting geodemographic areas to targeting individuals. Yet it inherits characteristics and problems from geodemographics, including a (...) justification through the market, and a process of commodification through the black-boxing of technology. As researchers develop sustained critiques of data analytics and its effects on everyday life, we must so with a grounding in the cultural and historical contexts from which data technologies emerged. This article and others develop a historically situated, critical approach to spatial Big Data. This history illustrates connections to the critical issues of surveillance, redlining, and the production of consumer subjects and geographies. The shared histories and structural logics of spatial Big Data and geodemographics create the space for a continued critique of data analyses’ role in society. (shrink)

With an estimated one billion smartphones producing over 5 petabytes of data a day, the spatially aware mobile device has become a near ubiquitous presence in daily life. Cogent, excellent research in a variety of fields has explored what the spatial data these devices produce can reveal of society, such as analysis of Foursquare check-ins to reveal patterns of mobility for groups through a city. In such studies, the individual intentions, motivations, and desires behind the production of said data can (...) become lost through computational aggregation and analysis. In this commentary, I argue for a rethinking of the epistemological leap from individual to data point through a seating of the reflexive, self-eliciting subject as an object for spatial big data research. To do so, I first situate current research on spatial big data within a computational turn in social sciences that relies overly on the data produced as a stand-in for the subject producing said data. Second, I argue that a recent shift within geography and cognate disciplines toward viewing spatial big data as a form of spatial media allows for study of the sociotechnical processes that produce modern assemblages of data and society. As spatial media, the spatial big data created through mobile device use can be understood as the data of everyday life and as part of the sociotechnical processes that produce individuals, data, and space. Ultimately, to understand the data of everyday life, researchers must write thick descriptions of the stories we tell ourselves about the data we give off to others. (shrink)