SACRO Logo

Welcome to the AI-SDC family of tools#

Our tools are designed to help researchers assess the privacy disclosure risks of their outputs, including tables, plots, statistical models, and trained machine learning models

ACRO (Python)

Statistical Disclosure Control for Python

Tools for the Semi-Automatic Checking of Research Outputs. Drop-in replacements for common analysis commands with built-in privacy protection.

https://jessuwe.github.io/ACRO/introduction.html
SACRO-ML

Machine Learning Privacy Tools

Collection of tools and resources for managing the statistical disclosure control of trained machine learning models.

https://jessuwe.github.io/SACRO-ML/introduction.html
ACRO-R

R Package Integration

R-language interface for the Python ACRO library, providing familiar R syntax for statistical disclosure control.

https://jessuwe.github.io/ACRO/introduction.html
SACRO Viewer

Graphical User Interface

A graphical user interface for fast, secure and effective output checking, which can work in any TRE (Trusted Research Environment).

Welcome to SACRO Viewer

SACRO Viewer: Graphical Output Review Tool#

SACRO Viewer is a desktop application for reviewing research outputs produced using the ACRO tools. It provides a graphical interface for output checkers to review files, researcher comments, and statistical analysis outcomes in a secure environment.

Note

Current Version: v0.1.0 - Cross-platform desktop application with Windows, Linux, and macOS support.

What is SACRO Viewer?#

SACRO Viewer is a desktop application that:

  • Loads JSON metadata output by ACRO tools for comprehensive output review

  • Displays research outputs with researcher comments and statistical analysis results

  • Allows output checkers to approve or reject individual outputs

  • Generates zipfiles containing only approved outputs for secure release

  • Works in Trusted Research Environments (TREs) without internet connectivity

Core Features#

Comprehensive Output Review#

  • ACRO Integration: Automatically detects and loads ACRO-generated metadata

  • File Display: View various file types including CSV, images, and text files

  • Statistical Context: See ACRO analysis results including disclosure risk assessments

  • Researcher Comments: Review comments and justifications provided by researchers

  • Approval Workflow: Individual approve/reject decisions for each output

  • Secure Release: Generate zipfiles containing only approved outputs

Design Principles#

  • Desktop Application: Runs locally without requiring internet connectivity

  • Cross-platform: Available for Windows, Linux, and macOS

  • TRE Compatible: Designed for use in secure Trusted Research Environments

  • User-friendly: Intuitive graphical interface for non-technical users

  • Secure: Local processing with no external data transmission

  • Audit Trail: Maintains records of approval decisions

Getting Started#

Install

Download and install SACRO Viewer for your operating system

Install
User Guide

Learn how to review outputs and manage approvals

User Guide
FAQ

Find answers to common questions

faq
Support

Get help and troubleshooting information

support

Key Components#

  • Output List: Browse all research outputs in a directory

  • File Viewer: Display output files with syntax highlighting and formatting

  • Review Panel: See ACRO status, comments, and make approval decisions

  • Release Manager: Generate approved output packages for secure release

Developer Resources#

Architecture

Understand the technical design and system components

architecture
Developer Guide

Set up development environment and contribute code

developer_guide
API Reference

Detailed documentation of classes and functions

api_reference

Community and Support#

Indices and tables#

Acknowledgement#

This work was supported by UK Research and Innovation as part of the Data and Analytics Research Environments UK (DARE UK) programme, delivered in partnership with Health Data Research UK (HDR UK) and Administrative Data Research UK (ADR UK). The specific projects were Semi-Automated Checking of Research Outputs (SACRO; MC_PC_23006), Guidelines and Resources for AI Model Access from TrusTEd Research environments (GRAIMATTER; MC_PC_21033), and TREvolution (MC_PC_24038). This project has also been supported by MRC and EPSRC (PICTURES; MR/S010351/1).