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ACRO: Tools for the Semi-Automatic Checking of Research Outputs

This repository maintains the ACRO R package, which is an interface to the Python ACRO package.

ACRO is a free and open source tool that supports the semi-automated checking of research outputs (SACRO) for privacy disclosure within secure data environments. SACRO is a framework that applies best-practice principles-based statistical disclosure control (SDC) techniques on-the-fly as researchers conduct their analysis. SACRO is designed to assist human checkers rather than seeking to replace them as with current automated rules-based approaches.

The ACRO package is a lightweight Python tool that sits over well-known analysis tools that produce outputs such as tables, plots, and statistical models. This package adds functionality to:

  • automatically identify potentially disclosive outputs against a range of commonly used disclosure tests;
  • apply optional disclosure mitigation strategies as requested;
  • report reasons for applying SDC;
  • and produce simple summary documents trusted research environment staff can use to streamline their workflow and maintain auditable records.

This creates an explicit change in the dynamics so that SDC is something done with researchers rather than to them, and enables more efficient communication with checkers.

A graphical user interface (SACRO-Viewer) supports human checkers by displaying the requested output and results of the checks in an immediately accessible format, highlighting identified issues, potential mitigation options, and tracking decisions made.

Additional programming languages such as this R package are supported by providing front-end packages that interface with the core ACRO Python back-end.

Installation

Prerequisite: you must have Python pre-installed.

Install the acro package from CRAN as follows:

install.packages("acro")

If you are having problems installing the package, please see the more detailed installation guide.

Usage

Before using any function from the package, an acro object should be initialised using the following R code:

library("acro")
acro_init(suppress = TRUE)

Try Online with MyBinder

Try an example notebook in RStudio online on MyBinder.org.

Select the example-notebook.Rmd in the bottom-right pane after loading.

Documentation

The github-pages contains pre-built documentation.

Additionally, see our paper describing the SACRO framework to learn about its principles-based SDC methodology and usage.

Acknowledgement

This work was funded by UK Research and Innovation under as part of the DARE UK (Data and Analytics Research Environments UK) programme, delivered in partnership with Health Data Research UK (HDR UK) and Administrative Data Research UK (ADR UK). The specific projects were:

  • Semi-Automatic Checking of Research Outputs (SACRO) [Grant Number MC_PC_23006] - a phase 1 Driver project
  • TREvolution [Grant Number MC_PC_24038] - phase 2:Transformative Components.

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Install

install.packages('acro')

Monthly Downloads

281

Version

0.1.7

License

MIT + file LICENSE

Issues

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Maintainer

Jim Smith

Last Published

February 2nd, 2026

Functions in acro (0.1.7)

acro_print_outputs

Prints the current results dictionary.
acro_remove_output

Remove outputs
acro_rename_output

Rename outputs
acro_surv_func

Survival analysis
acro_init

Initialise an ACRO object
acro_crosstab

Compute a simple cross tabulation of two (or more) factors.
lung

Lung Cancer Survival Data
acro_add_comments

Add comments to outputs
acro_finalise

Creates a results file for checking.
acro_hist

Histogram
acro_custom_output

Adds an unsupported output to the results dictionary
acro_add_exception

Adds an exception request to an output.
acro_enable_suppression

Turns suppression on during a session
acro_glm

Fits Logit or Probit model.
acro_disable_suppression

Turns suppression off during a session
acro_lm

Fits Ordinary Least Squares Regression
acro_pivot_table

Pivot table
acro_table

Compute a simple cross tabulation of two (or more) factors.
nursery_data

Nursery Database