Abstract: The rapid development of digital government initiatives necessitates secure open sharing of government big data while ensuring robust protection of personal information. To explore the implicit risks and explicitization strategies associated with personal information in the context of government big data will enhance collaborative supervision. Employing the data lifecycle theory, this study analyzes the stages of personal information management to identify inherent risks. It delves into the underlying technical, legal, subject-related, and value-related causes of these risks, emphasizing perceptible factors. The establishment of government big data centers provides a framework to articulate the implicit risks associated with personal information. The study focuses on developing strategies to mitigate process, usage, subject, and value-related risks, aiming to achieve a balanced approach to utilizing and safeguarding personal information within the government big data ecosystem, thereby strengthening regulatory oversight.