Speaker
Description
Space astronomy satellites serve as critical infrastructure in the field of astrophysics, and data processing is one of the most essential processes for conducting scientific research. The Institute of High Energy Physics (IHEP) of the Chinese Academy of Sciences has undertaken the development and construction of multiple space astronomy satellites, including HXMT, GECAM, SVOM, eXTP and CATCH. However, the growing volume and complexity of data from these satellites pose significant challenges for data processing. Traditional approaches rely heavily on manual intervention, featuring fixed, inflexible procedures that fail to satisfy the escalating data processing requirements of multi-satellite missions. To address this challenge, this study proposes an automated data processing workflow platform. The platform comprises three core modules: (1) visualized orchestration of data processing workflows; (2) automated scheduling and execution of data processing tasks; (3) real-time monitoring of workflow execution status. Through tests on the data processing pipelines of CATCH and eXTP, the effectiveness and practicability of the platform are verified. The platform can realize the automatic processing of satellite data, and improve the flexibility and execution efficiency of the data processing workflow, which is also suitable for multi-satellite data processing tasks.