This article considers how Spatial Big Data is situated and produced through embodied spatial experiences as data processes appear and act in small moments on mobile phone applications and other digital spatial technologies. Locating Spatial Big Data in the historical and geographical contexts of Sydney and Hong Kong, it traces how situated knowledges mediate and moderate the rising potency of discourses of cartographic reason and data logics as colonial cartographic imaginations expressed in land divisions and urban planning continue on, in (...) a world that increasingly values models of calculability, interoperability and authority. It draws on ethnographic material gathered through walking interviews in both cities, and in doing so, it argues that by using ethnographic ‘moments’, it is possible to decentre the focus on data processes to consider the critical potential of a politics of everyday experiences that produce and reflect the structures of data logics. Through these ethnographic moments, this article examines how mobile technologies are complicit in the production of Spatial Big Data, and the impact this has on the increasing regimentation and surveillance of modes of being and expression via mobile media. At the same time, it will argue that while spatial calculability has expanded from cartographic reason into data logics, the epistemological universality of Spatial Big Data is constantly being resisted – in moments of experimentation, failure, intuition, memory and desire, the ghosts of the incalculable epistemes, experiences and people, forgotten by the emphasis on calculation, continue to speak. (shrink)

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)

Recently, there has been renewed interest in so-called evidence-based policy making. Enticed by the grand promises of Big Data, public officials seem increasingly inclined to experiment with more data-driven forms of governance. But while the rise of Big Data and related consequences has been a major issue of concern across different disciplines, attempts to develop a better understanding of the phenomenon's historical foundations have been rare. This short commentary addresses this gap by situating the current push for numerical evidence within (...) a broader socio-political context, demonstrating how the epistemological claims of Big Data science intersect with specific forms of trust, truth, and objectivity. We conclude by arguing that regulators' faith in numbers can be attributed to a distinct political culture, a representative democracy undermined by pervasive public distrust and uncertainty. (shrink)

Recent buzzes around big data, data science and artificial intelligence portray a data-driven future for healthcare. As a response, Europe's key players have stimulated the use of big data technologies to make healthcare more efficient and effective. Critical Data Studies and Science and Technology Studies have developed many concepts to reflect on such overly positive narratives and conduct critical policy evaluations. In this study, we argue that there is also much to be learned from studying how professionals in the healthcare (...) field affectively engage with this strong European narrative in concrete big data projects. We followed twelve hospital-based big data pilots in eight European countries and interviewed 145 professionals between 2018 and 2020. In this study, we introduce the metaphor of dreams to describe how professionals link the big data promises to their own frustrations, ideas, values and experiences with healthcare. Our research answers the question: how do professionals in concrete data-driven initiatives affectively engage with European Union's data hopes in their ‘dreams’ – and with what consequences? We describe the dreams of being seen, of timeliness, of connectedness and of being in control. Each of these dreams emphasizes certain aspects of the grand narrative of big data in Europe, makes particular assumptions and has different consequences. We argue that including attention to these dreams in our work could help shine an additional critical light on the big data developments and stimulate the development of responsible data-driven healthcare. (shrink)

Predictive policing has become a new panacea for crime prevention. However, we still know too little about the performance of computational methods in the context of predictive policing. The paper provides a detailed analysis of existing approaches to algorithmic crime forecasting. First, it is explained how predictive policing makes use of predictive models to generate crime forecasts. Afterwards, three epistemologies of predictive policing are distinguished: mathematical social science, social physics and machine learning. Finally, it is shown that these epistemologies have (...) significant implications for the constitution of predictive knowledge in terms of its genesis, scope, intelligibility and accessibility. It is the different ways future crimes are rendered knowledgeable in order to act upon them that reaffirm or reconfigure the status of criminological knowledge within the criminal justice system, direct the attention of law enforcement agencies to particular types of crimes and criminals and blank out others, satisfy the claim for the meaningfulness of predictions or break with it and allow professionals to understand the algorithmic systems they shall rely on or turn them into a black box. By distinguishing epistemologies and analysing their implications, this analysis provides insight into the techno-scientific foundations of predictive policing and enables us to critically engage with the socio-technical practices of algorithmic crime forecasting. (shrink)

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.

Over the past two decades urban social life has undergone a rapid and pervasive geocoding, becoming mediated, augmented and anticipated by location-sensitive technologies and services that generate and utilise big, personal, locative data. The production of these data has prompted the development of exploratory data-driven computing experiments that seek to find ways to extract value and insight from them. These projects often start from the data, rather than from a question or theory, and try to imagine and identify their potential (...) utility. In this paper, we explore the desires and mechanics of data-driven computing experiments. We demonstrate how both locative media data and computing experiments are ‘staged’ to create new values and computing techniques, which in turn are used to try and derive possible futures that are ridden with unintended consequences. We argue that using computing experiments to imagine potential urban futures produces effects that often have little to do with creating new urban practices. Instead, these experiments promote Big Data science and the prospect that data produced for one purpose can be recast for another and act as alternative mechanisms of envisioning urban futures. (shrink)

This paper explores the variety of ways that emerging sources of data are being used to re-conceptualize the city, and how these understandings of what the urban is shapes the design of interventions into it. Drawing on work on the performativity of economics, this paper uses two vignettes of the ‘new urban science’ and municipal vacant property mapping in order to argue that the mobilization of Big Data in the urban context doesn’t necessarily produce a single, greater understanding of the (...) city as it actually is, but rather a highly variegated series of essentialized understandings of the city that render it knowable, governable and intervene-able. Through the construction of new, data-driven urban geographical imaginaries, these projects have opened up the space for urban interventions that work to depoliticize urban injustices and valorize new kinds of technical expertise as the means of going about solving these problems, opening up new possibilities for a remaking of urban space in the image of these sociotechnical paradigms. Ultimately, this paper argues that despite the importance of Big Data, as both a discourse and practice, to emerging forms of urban research and management, there is no singular or universal understanding of the urban that is promoted or developed through the application of these new sources of data, which in turn opens up meaningful possibilities for developing alternative uses of Big Data for understanding and intervening in the city in more emancipatory ways. (shrink)