Balancing Open Data and Privacy Protections

State Government case study

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Evinact worked to ensure the long-term security and privacy of sensitive datasets and create a culture of safe and secure data sharing within a state government department.

The context

Evinact was engaged by a large state government department after it was identified during a routine risk audit process that certain open datasets revealed privacy risks, meaning thousands of personal records were at risk of being identified. The department immediately remedied the affected open datasets to reduce the possibility of further risks.

Understanding the importance of data privacy, security and ethics to business operations and performance, the department turned to Evinact for assistance. We were engaged to provide assurance that the department’s privacy risk remediation efforts had been effective and mitigated any future privacy risks.

The method

We engaged with department stakeholders to conduct an independent review of the existing risk assessment and the department’s remediation response. Using the same method as the auditor, Evinact determined whether or not an individual could be re-identified by combining information across attributes combined with adversarial knowledge. We conducted the risk assessment based on the existence of unique records identifiable in datasets and the level of privacy risk posed and collated our findings to deliver the department with a robust and proven framework for improving open data privacy.

In doing this, we were able to identify any new privacy risks in the datasets that had surfaced as a result of the remediation efforts and provide recommendations for future practices regarding the department’s privacy-preserving practices in relation to open data publication.

The impact

Evinact enabled the department to confidently publish de-identified datasets by providing assurance that re-identification risks had been appropriately assessed and mitigated. This strengthened the department’s ability to share data safely and responsibly, supporting transparency, research and evidence-based decision-making while maintaining strong privacy protections and public trust.

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This engagement was originally completed as GWI.

Michelle Teis

Michelle is a senior executive with 30 years of leadership experience in data strategy, governance, management and analytics. With a strong foundation in promoting data-driven decision-making, Michelle is a trusted advisor to other C-Suite executives.​

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