Stefan Bender, Ron S. Jarmin, Frauke Kreuter, Julia Lane
Privacy and Confidentiality

S. 313-332 in: Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, Julia Lane (Hrsg.): Big Data and Social Science: Data Science Methods and Tools for Research and Practice. 2nd edition 2021. New York: CRC Press
[CRC Statistics in Social and Behavioral Sciences]

This chapter addresses the issue that sits at the core of any study of human beings—ensuring that the privacy and confidentiality of the people and organizations being studied is protected appropriately. In practical terms, the study of human subjects requires that the interests of individual privacy and data confidentiality be balanced against the social benefits of research access and use. The challenge faced by social science researchers relative to data users in other contexts is the need to compute accurate statistics from sensitive databases, share their results broadly and facilitate scientific review and replication. The approaches to providing access have evolved over time. Statistical agencies often employ a range of approaches depending on the needs of heterogeneous data users. Statistical agencies have made data available in a number of ways: through tabular data, public use files, licensing agreements and, more recently, through synthetic data.