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Statistical Disclosure Control (sdcMicro)


SDCMicro is free, R-based open-source package for the generation of protected microdata for researchers and public use. Data from statistical agencies and other institutions are mostly confidential. This package can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. In addition, various risk estimation methods are included. The associated package sdcMicroGUI includes a graphical user interface for various methods in the sdcMicro package.


Templ M, Kowarik A, Meindl B (2015). “Statistical Disclosure Control for Micro-Data Using the R Package sdcMicro.” Journal of Statistical Software, 67(4), 1–36. doi: 10.18637/jss.v067.i04


Matthias Templ (matthias.templ at


R-based free, open-source package distributed under GPL 2.0 license Graphical user interface available for users with no or limited knowledge of the R language
Multiple options for reducing disclosure risk and for assessing information loss Multiple methods for assessing the re-identification risk (k-anonymity, individual, and global re-identification risk)

System Requirements

sdcMicro requires a PC running MS-Windows XP, Windows Vista, Windows 7, Windows 8, Mac OS X or Unix/Linux.

Recent Developments

Funding from the World Bank and DFID has been used to fund the development of a new Graphic User Interface for the open-source R package sdcMicro. For users comfortable with using R, the package sdcMicro provides a tool for the application of a comprehensive suite of methods commonly used and described in the literature on disclosure control. Users not familiar with R, but who have an immediate need for tools to anonymize microdata, would benefit from a friendly Graphic User Interface (GUI) for the sdcMicro package. To provide a GUI environment for the non-R user, a Shiny application called sdcApp has been added to the sdcMicro package. Users of sdcApp are able to implement the most widely used anonymization methods present in the sdcMicro package without requiring in-depth knowledge of R. In addition to the anonymization methods implemented in the sdcMicro package, sdcApp offers a comprehensive set of risk and utility measures. This includes functions to measure, visualize and compare risk and utility throughout the anonymization process. sdcApp also helps users by producing reports on the methods used in formats suitable for internal and external audiences and saves the underlying R code to ensure reproducibility. For users of other statistical packages, sdcApp supports importing and exporting microdata in several formats (STATA, SAS, SPSS, CSV, R). Like R, sdcMicro is open source and available in the CRAN repositories and on GitHub.


Version: 5.4.1

Date: 2018-04-13

License: GPL 2.0

Development URL:

The software and its documentation can be downloaded from the following link: