Many national statistical agencies, survey organizations, and researchers – henceforth all called agencies – collect data that they intend to share with others. Wide dissemination of data facilitates advances in science and public policy, enables students to develop skills at data analysis, and helps ordinary citizens learn about their communities. Often, however, agencies cannot release data as collected, because doing so could reveal data subjects’ identities or values of sensitive attributes. Failure to protect confidentiality can have serious consequences for agencies, since they may be violating laws or institutional rules enacted to protect confidentiality. Additionally, when confidentiality is compromised, the agencies may lose the trust of the public, so that potential respondents are less willing to give accurate answers, or even to participate, in future studies (Reiter 2004).
At first glance, sharing safe data with others seems a straightforward task: simply strip unique...
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References and Further Reading
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Reiter, J.P. (2011). Statistical Approaches to Protecting Confidentiality in Public Use Data. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_537
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