The Israeli Ministry of Health released microdata of live births in Israel in 2014, processed to protect the privacy of mothers and newborns. The dataset, based on the National Registry of Live Births, was co-designed with stakeholders and released using differential privacy. The dataset includes 165,915 records of singleton births, with six selected data fields. The release was designed to meet stakeholder requirements for privacy, accuracy, and microdata format. Differential privacy was used to ensure privacy, with a total privacy loss budget of ε = 9.98. The synthetic data was generated using the PrivBayes algorithm, and the release was evaluated against a set of acceptance criteria, including faithfulness, accuracy of statistical queries, and face privacy. The dataset was made publicly available, along with documentation and code, to ensure transparency and usability. The release demonstrated the feasibility of using differential privacy for government data, balancing privacy and utility while meeting stakeholder expectations. The project highlights the challenges and considerations in releasing differentially private data, including the need for rigorous privacy guarantees, accurate statistical queries, and trustworthiness. The release also underscores the importance of stakeholder involvement in defining requirements and ensuring the success of privacy-preserving data releases.The Israeli Ministry of Health released microdata of live births in Israel in 2014, processed to protect the privacy of mothers and newborns. The dataset, based on the National Registry of Live Births, was co-designed with stakeholders and released using differential privacy. The dataset includes 165,915 records of singleton births, with six selected data fields. The release was designed to meet stakeholder requirements for privacy, accuracy, and microdata format. Differential privacy was used to ensure privacy, with a total privacy loss budget of ε = 9.98. The synthetic data was generated using the PrivBayes algorithm, and the release was evaluated against a set of acceptance criteria, including faithfulness, accuracy of statistical queries, and face privacy. The dataset was made publicly available, along with documentation and code, to ensure transparency and usability. The release demonstrated the feasibility of using differential privacy for government data, balancing privacy and utility while meeting stakeholder expectations. The project highlights the challenges and considerations in releasing differentially private data, including the need for rigorous privacy guarantees, accurate statistical queries, and trustworthiness. The release also underscores the importance of stakeholder involvement in defining requirements and ensuring the success of privacy-preserving data releases.