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Investigating privacy and confidentiality risks in ISC data

Data privacy and confidentiality training.

Project start date: 20 March 2022
Project end date: 24 July 2022
Publication date: 07 February 2023
Project status: Completed
Livestock species: Grain-fed Cattle, Grass-fed Cattle, Sheep, Goat, Lamb
Relevant regions: National
Download Report (0.4 MB)


The aim of this project is to identify and understand:

  • The privacy and confidentiality risks of ISC data
  • The efficacy of data treatment techniques when sharing data to reduce risks
  • The ideal development processes and techniques in line with best practice data sharing.


This project aims to deliver the following:

  • Assess current data deidentification processes and assess risk level
  • Identify identifiable and quasi-identifiable fields of data commonly used in ISC datasets
  • Create a toolbox of processes for ISC to use to assess risk of de-identification of datasets
  • Build internal ISC capability around the processes of assessing data sharing risks and deidentification procedures
  • Build internal ISC capability of the processes required to safely share data to minimise risk of identification of individuals.

Key findings

A toolbox and training sessions were delivered to allow MLA staff to consider risk of releasing data depending on:

  • The amount of data
  • The requestor
  • The purpose and environment.

There is a conservative approach to data release, driven by ISC obligations as custodians of industry data and stakeholder (producer) expectations associated with the sensitivities of animal movement and related business activities. Data release beyond ISC involves a complex process, driven by stakeholder groups and ISC policy.
An output of this work was some suggestions on how to optimise the way data is utilised and controlled while maintaining the level of privacy and due diligence.

Benefits to industry

This project will enable ISC to share data to research organisations, supply chain participants and commercial companies within the red meat industry. This is done to:

  • Enable innovation
  • Gather data and insights
  • Minimise data sharing risks and enabling compliance to ISC's data sharing policies.

Future research

For more information

Contact Project Manager: Hayley Robinson