5.1 Variables

The following list of variables is important to consider when preparing data for release.

Personal Characteristics

• Age

• Sex

• Race

• Ethnicity

• Language Spoken

• Location of Residence

• Education Status

• Financial Status

Event Characteristics

• Number of events

• Location of event

• Time period of event

• Provider of event

As stated previously, variables that are personal characteristics may be used to determine a person’s identity or attributes. When these characteristics are used to confirm the identity of an individual in a publicly released data set, then a disclosure of an individual’s information has occurred. Individual uniqueness in the released data and in the population is a quality that helps distinguish one person from another and is directly related to re-identification of individuals in aggregate data. Disclosure risk is a concern when released data reveal characteristics that are unique in both the released data and in the underlying population. The risk of re-identifying an individual or group of individuals increases when unique or rare characteristics are “highly visible”, or otherwise available without any special or privileged knowledge. Unique or rare personal characteristics (e.g., height above 7 feet) or information that isolate individuals to small demographic subgroups (e.g., American Indian Tribal membership) increase the likelihood that someone can correctly attribute information in the released data to an individual or group of individuals.

Variables that are event characteristics are often associated with publicly available information.

Therefore, increased risk occurs when personal characteristics are combined with enough granularity with event characteristics. One could argue that if no more than two personal characteristics are combined with event characteristics then the risk will be low independent of the granularity of the variables. This hypothesis will need to be tested using various population frequencies to quantify the uniqueness of the combination of variables both the in the potential data to be released as well as in the underlying population.