Internet and telecommunications, ubiquitous sensing devices, and advances in data storage and analytic capacities have heralded the age of Big Data, where the volume, velocity, and variety of data not only promise new opportunities for the harvesting of information, but also threaten to overload existing resources for making sense of this information. The use of Big Data technology for criminal justice and crime control is a relatively new development. Big Data technology has overlapped with criminology in two main areas: (a) Big Data is used as a type of data in criminological research, and (b) Big Data analytics is employed as a predictive tool to guide criminal justice decisions and strategies. Much of the debate about Big Data in criminology is concerned with legitimacy, including privacy, accountability, transparency, and fairness.
Big Data is often made accessible through data visualization. Big Data visualization is a performance that simultaneously masks the power of commercial and governmental surveillance and renders information political. The production of visuality operates in an economy of attention. In crime control enterprises, future uncertainties can be masked by affective triggers that create an atmosphere of risk and suspicion. There have also been efforts to mobilize data to expose harms and injustices and garner support for resistance. While Big Data and visuality can perform affective modulation in the race for attention, the impact of data visualization is not always predictable. By removing the visibility of real people or events and by aestheticizing representations of tragedies, data visualization may achieve further distancing and deadening of conscience in situations where graphic photographic images might at least garner initial emotional impact.
Article
Daniel T. O'Brien
In recent years, a variety of novel digital data sources, colloquially referred to as “big data,” have taken the popular imagination by storm. These data sources include, but are not limited to, digitized administrative records, activity on and contents of social media and internet platforms, and readings from sensors that track physical and environmental conditions. Some have argued that such data sets have the potential to transform our understanding of human behavior and society, constituting a meta-field known as computational social science. Criminology and criminal justice are no exception to this excitement. Although researchers in these areas have long used administrative records, in recent years they have increasingly looked to the most recent versions of these data, as well as other novel resources, to pursue new questions and tools.
