Privacy in confidential administrative micro data: implementing statistical disclosure control in a secure computing environment.
The demand for comprehensive and innovative data is constantly growing in social science. In particular, micro data from various social security agencies become more and more attractive. In contrast to survey data, administrative data offer a census with highly reliable information but are restricted in their usage. To make them accessible for researchers, data or research output either have to be anonymized or released after disclosure review procedures have been used. This article discusses the trade-off between maintaining a high capability of research potential while protecting private information, by exploiting the data disclosure portfolio and the adopted disclosure strategies of the Research Data Center of the German Federal Employment Agency.
Institute for Social Research, University of Michigan, Ann Arbor, MI, USA danielah@umich.edu.
Daniela
D
Hochfellner
Institute for Employment Research, Nürnberg, Germany.
Dana
D
Müller
Institute for Employment Research, Nürnberg, Germany.
Alexandra
A
Schmucker
D019352:Censuses; D016494:Computer Security; D003219:Confidentiality; D003625:Data Collection / Q000941:ethics* / Q000379:methods; D030881:Disclosure; D032984:Ethics, Research; D005858:Germany; D006077:Government Agencies; D006801:Humans; D037141:Mandatory Programs; D018907:Privacy; D011996:Records; D012106:Research; D012107:Research Design; D012942:Social Sciences; D012943:Social Security
administrative data; anonymization; confidentiality; data protection; social sciences