Abstract
This research focuses on the way Dutch immigrant populations are ‘datafied’ by various societal institutions. Classifications are based on immigrants’ former nationality or that of their parents and relate to the (postcolonial) history of their country of birth. This analysis starts with an investigation of the datafication of racial and ethnic information and its distribution by the Statistics Netherlands (CBS). Next, race and ethnicity based data-driven practices will be mapped in three domains: local government, the police and commercial information systems. This research will be carried out in the form of discursive analyses of (1) the categorization system of CBS, (2) the distribution system of CBS and its interface, and (3) the applications in which CBS data is appropriated for a new purpose. The first case study is the Leefbaarometer. This interactive map of the Netherlands visualizes the quality of life down to street level and is used as an in instrument by local governments for determining the necessity for action in certain neighbourhoods. The second case study is the Crime Anticipation System (CAS), which is used by the Dutch police to manage manpower and material resources. The final case study is the Allochtoon-o-meter by Geenstijl, a webapp in which the user enters a postcode and is shown the percentage of “non-western” immigrants living in that area. The three case studies serve as input for a reflective framework for evaluating data-driven policies at various levels of government