Open Science and Open Government at RIVM: A Balancing Act between Data Privacy and Utility

The Dutch National Institute for Public Health and the Environment (RIVM) addresses the challenges of Open Data, Open Government, and Open Science through the use of Statistical Disclosure Control (SDC). SDC minimizes re-identification risks in data sharing while preserving data utility, a balance that involves assessing risks, applying anonymization techniques, and measuring information loss. Given the complexity of these tasks and the diverse nature of the data handled by RIVM, simple, universal rules are insufficient. Instead, RIVM has formed a multidisciplinary SDC working group consisting of data stewards, statisticians, and privacy experts. This team not only advises on but also creates guidelines for SDC, enhancing organizational knowledge through training and presentations. They use the open-source tool sdcMicro to aid their operations. This lightning talk will delve into how RIVM implements SDC, with a particular focus on examples from the COVID-19 pandemic, illustrating the shifting landscape of data sharing expectations. The talk demonstrates RIVM's strategies for maintaining public trust and meeting ethical and legal standards while promoting transparency and advancing Open Science and Government initiatives.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-19
DOI
https://doi.org/10.5281/zenodo.14975657
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.00
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article

Open Science and Open Government at RIVM: A Balancing Act between Data Privacy and Utility

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

Open Science and Open Government at RIVM: A Balancing Act between Data Privacy and Utility

article en

Abstract

The Dutch National Institute for Public Health and the Environment (RIVM) addresses the challenges of Open Data, Open Government, and Open Science through the use of Statistical Disclosure Control (SDC). SDC minimizes re-identification risks in data sharing while preserving data utility, a balance that involves assessing risks, applying anonymization techniques, and measuring information loss. Given the complexity of these tasks and the diverse nature of the data handled by RIVM, simple, universal rules are insufficient. Instead, RIVM has formed a multidisciplinary SDC working group consisting of data stewards, statisticians, and privacy experts. This team not only advises on but also creates guidelines for SDC, enhancing organizational knowledge through training and presentations. They use the open-source tool sdcMicro to aid their operations. This lightning talk will delve into how RIVM implements SDC, with a particular focus on examples from the COVID-19 pandemic, illustrating the shifting landscape of data sharing expectations. The talk demonstrates RIVM's strategies for maintaining public trust and meeting ethical and legal standards while promoting transparency and advancing Open Science and Government initiatives.

Zenodo (CERN European Organization for Nuclear Research)
National Institute for Public Health and the Environment (NL)
Openalex Percentile: Top 43%
Research Data Management Practices
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