De-identification removes identifying information from a dataset so that the remaining data cannot be linked with specific individuals. Government agencies can use de-identification to reduce the privacy risk associated with collecting, processing, archiving, distributing or publishing government data. Previously NIST published NISTIR 8053, “De-Identifying Personal Data,” which provided a survey of de-identification and re-identification techniques. This document provides specific guidance to government agencies that wish to use de-identification. Before using de-identification, agencies should evaluate their goals in using de-identification and the potential risks that de-identification might create. Agencies should decide upon a de-identification release model, such as publishing de-identified data, publishing synthetic data based on identified data, and providing a query interface to identified data that incorporates de-identification. Agencies can use a Disclosure Review Board to oversee the process of de-identification; they can also adopt a de-identification standard with measurable performance levels. Several specific techniques for de-identification are available, including de-identification by removing identifiers and transforming quasi-identifiers and the use of formal de-identification models that rely upon Differential Privacy. De-identification is typically performed with software tools which may have multiple features; however, not all tools that mask personal information provide sufficient functionality for performing de-identification. This document also includes an extensive list of references, a glossary, and a list of specific de-identification tools, although the mention of these tools is only to be used to convey the range of tools currently available, and is not intended to imply recommendation or endorsement by NIST.