Demographic/Other Data

This page talks about protection methods for demographic, educational, and other non-health and non-tax data types. These data typically contain information that could be available to the public; for example, geography, age, race, gender, marital status, and property taxes. If these variables are released without alteration, it may be possible for malicious data users to link names to these records by matching to external data sources. For example, Sweeney (1997) showed that 97% of the records in a medical database for Cambridge, MA, could be identified using only birth date and 9-digit ZIP code by linking them to a publicly available voter registration list. However, many times these data are samples rather than censuses. Sampling protects individuals because it is not certain whether a targeted individual was collected in the data.

Most of the typical alteration strategies can be applied on demographic/other data; see the web page on data protection methods for explanation of the methods. Often agencies apply multiple methods on the same dataset. Below are links to illustrative applications of confidentiality protections on demographic/other data. This list is by no means exhaustive, but it does illustrate the techniques typically used to protect these data.