Conceptual design of new data integration and process system for KSTAR data scheduling

Abstract The KSTAR control and data acquisition systems mainly use data storage layer of MDSPlus for diagnostic data and channel archiver for EPICS-based control system data. In addition to these storage systems, KSTAR has various types of data such as user logs from Relational Database (RDB) and various types of logs from the control system. A large scientific machine like KSTAR is needed to implement various types of use cases for scheduling data and data analysis. The goal of a new data integration and process system is to design the KSTAR data scheduling on top of the Pulse Automation and Scheduling System (PASS) according to KSTAR events. The KSTAR Data Integration System (KDIS) is designed by using Big Data software infrastructures and frameworks. The KDIS handles events that are synchronized with the KSTAR EPICS events and other data sources such as the rest API and logs for integrating and processing data from different data sources and for visualizing data. In this paper, we explain the detailed design concept of KDIS and demonstrate a data scheduling use case with this system.