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

Navigation

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for jim-smith from gravatar.com jim-smith Avatar for rpreen from gravatar.com rpreen

Unverified details

These details have not been verified by PyPI
Meta
  • License Expression: MIT
    SPDX License Expression
  • Maintainer: Jim Smith
  • Tags data-privacy , data-protection , privacy , privacy-tools , statistical-disclosure-control , statistical-software
  • Requires: Python >=3.10
  • Provides-Extra: doc , test
Classifiers
Report project as malware

Project description

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

IEEE Xplore PyPI package Conda Python versions codecov

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 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.

ACRO workflow and architecture schematic

Installation

ACRO is available through PyPI and Conda.

If installed in this way, the examples and data files used therein will need to be copied from the repository.

PyPI:

$ pip install acro

Conda:

$ conda install acro

Examples

See the example notebooks for:

Try Online with MyBinder

Try an example notebook online on MyBinder.org.

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.

Training Materials

For training videos about ACRO, see training videos.

Contributing

See CONTRIBUTING.md

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.

Project details

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for jim-smith from gravatar.com jim-smith Avatar for rpreen from gravatar.com rpreen

Unverified details

These details have not been verified by PyPI
Meta
  • License Expression: MIT
    SPDX License Expression
  • Maintainer: Jim Smith
  • Tags data-privacy , data-protection , privacy , privacy-tools , statistical-disclosure-control , statistical-software
  • Requires: Python >=3.10
  • Provides-Extra: doc , test
Classifiers

Release history Release notifications | RSS feed

This version

0.4.12

0.4.11

0.4.10

0.4.9

0.4.8

0.4.7

0.4.6

0.4.5

0.4.3

0.4.2

0.4.0

0.3.0

0.2.0

0.1.0

0.0.6

0.0.5

0.0.4

0.0.3

0.0.2

0.0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

acro-0.4.12.tar.gz (56.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

acro-0.4.12-py3-none-any.whl (36.1 kB view details)

Uploaded Python 3

File details

Details for the file acro-0.4.12.tar.gz.

File metadata

  • Download URL: acro-0.4.12.tar.gz
  • Upload date:
  • Size: 56.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for acro-0.4.12.tar.gz
Algorithm Hash digest
SHA256 3cd6039fb17915d7b0c76bd4cd44e89cd5caee364bf8a31e211314931dea05d1
MD5 c4edf5c79b5a94e6635ded2bd6f83e8c
BLAKE2b-256 70f3cf85bb7eef6f51fac8b205be9dc0f0365df77df7e7b6ac743218fe800a19

See more details on using hashes here.

Provenance

The following attestation bundles were made for acro-0.4.12.tar.gz:

Publisher: pypi.yml on AI-SDC/ACRO

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file acro-0.4.12-py3-none-any.whl.

File metadata

  • Download URL: acro-0.4.12-py3-none-any.whl
  • Upload date:
  • Size: 36.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for acro-0.4.12-py3-none-any.whl
Algorithm Hash digest
SHA256 cd5f0aaf5f3f4f606903cb486da2d0b2b13a9abc8d15eb771c16fe03b0bc9399
MD5 f889e0ae8e6e37d2bb89190a7eee5e22
BLAKE2b-256 369d83ad65d36616da916624ebc7ec34f6ddba5fb6707d9d89831c84b1fd8024

See more details on using hashes here.

Provenance

The following attestation bundles were made for acro-0.4.12-py3-none-any.whl:

Publisher: pypi.yml on AI-SDC/ACRO

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page