Abstract: Objectives： The rapid growth of intelligent connected vehicles (ICV) has led to a sharp increase in multi-modal spatiotemporal data acquired through onboard sensors. While these data are critical for enabling autonomous driving and intelligent transportation, their high-frequency collection and dynamic flow raise concerns regarding geoinformation security, personal privacy, and compliance with regulatory frameworks. Fragmented oversight among enterprises, compliance technology service providers, and regulators hampers lawful data circulation and transparent governance. This paper aims to design a lifecycle compliance supervision framework for ICV spatiotemporal data that can support multi-subject coordination and full-process regulatory control. Methods： To address these issues, a third-party-led compliance supervision platform design is proposed. The platform is organized under a three-tier management structure of “national-regional-enterprise” and includes three core interfaces for regulatory authorities, ICV enterprises, and compliance support units. Within this organizational framework, regulatory authorities are responsible for rule transmission, review organization, and supervisory enforcement; ICV enterprises serve as the primary actors for data declaration, compliant operation, and responsibility fulfillment; and compliance support units provide technical support for policy implementation and scenario adaptation. A closed-loop mechanism is established, comprising pre-use review, real-time monitoring, and post-event auditing. It covers the entire data lifecycle, including collection, transmission, storage, processing, usage, sharing, cross-border transfer, and destruction. To support differentiated supervision, the platform design is developed to be compatible with existing policies, regulations, standards, and draft specifications for ICV spatiotemporal data governance, while remaining extensible to accommodate evolving regulatory requirements and application scenarios. In particular, current requirements related to data classification and grading, geoinformation security, and lifecycle governance are incorporated into the design logic of the platform. In addition, data provenance is adopted as the core supporting technology, and a structured provenance logging framework is designed to record key lifecycle information such as task execution, data operations, responsible subjects, and review status, thereby supporting process reconstruction and responsibility tracing. Results： Prototype-based validation was conducted in three representative scenarios, namely collection task application, process behavior monitoring, and anomalous event appeal handling. The results show that the proposed platform can support task access review before data activities begin, process supervision during task execution, and responsibility tracing with appeal disposition after abnormal events occur. It also improves supervision transparency and supports coordinated regulation across multiple subjects. Conclusions： The proposed framework provides a regulation-aligned and operationally feasible approach to the compliance supervision of ICV spatiotemporal data. By integrating lifecycle governance, differentiated control, and provenance-based traceability into a unified platform, it offers methodological support for the systematic implementation of relevant regulatory mechanisms in intelligent connected vehicle scenarios.