FAIR-MAST: A fusion device data management system

<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.

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Publication Details

Journal
SoftwareX
Published
2024-09-01
DOI
https://doi.org/10.1016/j.softx.2024.101869
Citations
9
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
7.01

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article

FAIR-MAST: A fusion device data management system

James Hodson, R. Akers, Jeyan Thiyagalingam, Saiful Khan et al.
9 citations
SoftwareX
Research Data Management Practices
7.01
article

FAIR-MAST: A fusion device data management system

James Hodson, R. Akers, Jeyan Thiyagalingam, Saiful Khan, Nathan Cummings, Shaun de Witt, S. Pamela, Samuel Jackson
article en
9 citations

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.

SoftwareXVol. 27
Rutherford Appleton Laboratory (GB), Science and Technology Facilities Council (GB), Culham Centre for Fusion Energy (GB), Culham Science Centre (GB), United Kingdom Atomic Energy Authority (GB)
UK Atomic Energy Authority, Engineering and Physical Sciences Research Council, Science and Technology Facilities Council
Openalex Percentile: Top 3%
Research Data Management Practices
7.01
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