‘For good measure’: data gaps in a big data world

Policy and data scientists have paid ample attention to the amount of data being collected and the challenge for policymakers to use and utilize it. However, far less attention has been paid towards the quality and coverage of this data specifically pertaining to minority groups. The paper makes the argument that while there is seemingly more data to draw on for policymakers, the quality of the data in combination with potential known or unknown data gaps limits government’s ability to create inclusive policies. In this context, the paper defines primary, secondary, and unknown data gaps that cover scenarios of knowingly or unknowingly missing data and how that is potentially compensated through alternative measures. Based on the review of the literature from various fields and a variety of examples highlighted throughout the paper, we conclude that the big data movement combined with more sophisticated methods in recent years has opened up new opportunities for government to use existing data in different ways as well as fill data gaps through innovative techniques. Focusing specifically on the representativeness of such data, however, shows that data gaps affect the economic opportunities, social mobility, and democratic participation of marginalized groups. The big data movement in policy may thus create new forms of inequality that are harder to detect and whose impact is more difficult to predict.