From f536012548a8aefb8d170f5c265966d77d3350db Mon Sep 17 00:00:00 2001 From: Richard Preen Date: Wed, 20 Nov 2024 10:15:26 +0000 Subject: [PATCH] update README --- README.md | 20 +++++++++++--------- 1 file changed, 11 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index 743cba9..17a0396 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -## ACRO: Tools for the Automatic Checking of Research Outputs +## ACRO: Tools for the Semi-Automatic Checking of Research Outputs [![DOI](https://zenodo.org/badge/534172863.svg)](https://zenodo.org/badge/latestdoi/534172863) [![PyPI package](https://img.shields.io/pypi/v/acro.svg)](https://pypi.org/project/acro) @@ -6,18 +6,20 @@ [![Codacy](https://app.codacy.com/project/badge/Grade/a125e023fd7744d79cb42cd31f6ea05e)](https://app.codacy.com/gh/AI-SDC/ACRO/dashboard) [![codecov](https://codecov.io/gh/AI-SDC/ACRO/branch/main/graph/badge.svg?token=VVHI41N05F)](https://codecov.io/gh/AI-SDC/ACRO) -This repository holds the Python ACRO package. An R wrapper package is available: [ACRO-R](https://github.com/AI-SDC/ACRO-R). +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](https://en.wikipedia.org/wiki/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. -A GUI for viewing and approving outputs is also available: [SACRO-Viewer](https://github.com/AI-SDC/SACRO-Viewer) +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: -ACRO (Automatic Checking of Research Outputs) is an open source tool for automating the [statistical disclosure control](https://en.wikipedia.org/wiki/Statistical_disclosure_control) (SDC) of research outputs. ACRO assists researchers and output checkers by distinguishing between research output that is safe to publish, output that requires further analysis, and output that cannot be published because of a substantial risk of disclosing private data. +* 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. -It does this by providing a lightweight 'skin' that sits over well-known analysis tools, in a variety of languages researchers might use. This adds functionality to: +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. -* identify potentially disclosive outputs against a range of commonly used disclosure tests; -* suppress outputs where required; -* report reasons for suppression; -* produce simple summary documents TRE staff can use to streamline their workflow. +A graphical user interface ([SACRO-Viewer](https://github.com/AI-SDC/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 analytical programming languages used by researchers are supported by providing front-end packages that interface with the core ACRO Python back-end; for example, see the R wrapper package: [ACRO-R](https://github.com/AI-SDC/ACRO-R). ![ACRO workflow and architecture schematic](docs/schematic.png)