Confidentiality

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There is a growing recognition within many sectors of Australian society that data is a strategic resource. The Australian Government Public Data Policy Statement acknowledges that data 'holds considerable value for growing the economy, improving service delivery and transforming policy outcomes for the nation'.

Organisations that collect data, including the Australian Bureau of Statistics (ABS), are being encouraged to make their data holdings more widely available. This includes releasing aggregate and unit record datasets (microdata) in ways that optimise their usefulness while still protecting the secrecy and privacy of those providing the information as required by Australian legislation. This series focusses on methods and management techniques to securely release data while maintaining the confidentiality of individuals or organisations about which the information relates.

The Australian Bureau of Statistics has safely and effectively made data holdings available for over 110 years. By law the ABS must disseminate official statistics while making sure that information is not released in a way that is likely to enable individuals or organisations to be identified.

The Confidentiality Information Series was first released in 2009 as part of the Cross Portfolio Statistical Data Integration Initiative. The ABS worked with data partners in the National Statistical Service to release the Series to provide guidance on how to safely maximise the usefulness of datasets for statistical and research purposes. The Series has now been updated in this second release.

The updated Series provides a brief legislative background to keeping data confidential, explains how to assess and manage confidentiality risks by using tools such as the Five Safes Framework, and outlines methods for treating data as part of this risk management approach.

Parts 1—3 are intended as a non-technical introduction. They provide conceptual background on approaches to managing data access for statistical and research purposes and the re-identification risks that occur in a statistical context.

Parts 4—5 provide statistical guidance and explain statistical methods for treating data to protect confidentiality, while Part 6 provides an example of the potential impact of data treatment on research.

Important note: All data examples (except those noted in Part 6 which use published data) presented in these sheets are entirely invented.