FAIR-MAST: A fusion device data management system
Samuel Jackson, Saiful Khan, Nathan Cummings, James Hodson, Shaun de Witt, S. Pamela, R. Akers, Jeyan Thiyagalingam
Abstract
<h2>Abstract</h2> We are introducing FAIR-MAST, a data management system designed for historical diagnostic data from the Mega Ampere Spherical Tokamak (MAST) fusion experiments. Following the FAIR (findability, accessibility, interoperability, and re-usability) principles, our system aims to address current accessibility issues with data that supports artificial intelligence and machine learning (AI/ML) and advanced data analysis. The system features public APIs with a searchable metadata index and object storage for remote data access. The API integrates a high-performance data analysis stack for scalable data analysis and AI/ML application development. Performance analysis demonstrates a tenfold improvement in data access speed compared to the legacy system, enabling more efficient and comprehensive data exploration. Additionally, our system is designed to be adaptable to other tokamak facilities, such as MAST-Upgrade (MAST-U) and the Joint European Torus (JET), to expedite fusion energy research and promote collaboration.