An Open Data Service for Supporting Research in Machine Learning on Tokamak Data

Samuel Jackson; Saiful Khan; Nathan Cummings; James Hodson; Shaun De Witt; Stanislas Pamela; Rob Akers; Jeyan Thiyagalingam; A. Kirk; J. Adamek; R. J. Akers; S. Allan; L. Appel; F. Arese Lucini; M. Barnes; T. Barrett; N. Ben Ayed; W. Boeglin; J. Bradley; P. K. Browning; J. Brunner; P. Cahyna; S. Cardnell; M. Carr; F. Casson; M. Cecconello; C. Challis; I. T. Chapman; S. Chapman; J. Chorley; S. Conroy; N. Conway; W. A. Cooper; M. Cox; N. Crocker; B. Crowley; G. Cunningham; A. Danilov; D. Darrow; R. Dendy; D. Dickinson; W. Dorland; B. Dudson; D. Dunai; L. Easy; S. Elmore; M. Evans; T. Farley; N. Fedorczak; A. Field; G. Fishpool; I. Fitzgerald; M. Fox; S. Freethy; L. Garzotti; Y. C. Ghim; K. Gi; K. Gibson; M. Gorelenkova; W. Gracias; C. Gurl; W. Guttenfelder; C. Ham; J. Harrison; D. Harting; E. Havlickova; N. Hawkes; T. Hender; S. Henderson; E. Highcock; J. Hillesheim; B. Hnat; J. Horacek; J. Howard; D. Howell; B. Huang; K. Imada; M. Inomoto; R. Imazawa; O. Jones; K. Kadowaki; S. Kaye; D. Keeling; I. Klimek; M. Kocan; L. Kogan; M. Komm; W. Lai; J. Leddy; H. Leggate; J. Hollocombe; B. Lipschultz; S. Lisgo; Y. Q. Liu; B. Lloyd; B. Lomanowski; V. Lukin; I. Lupelli; G. Maddison; J. Madsen; J. Mailloux; R. Martin; G. McArdle; K. McClements; B. McMillan; A. Meakins; H. Meyer; C. Michael; F. Militello; J. Milnes; A. W. Morris; G. Motojima; D. Muir; G. Naylor; A. Nielsen; M. O'Brien; T. O'Gorman; M. O'Mullane; J. Olsen; J. Omotani; Y. Ono; S. Pamela; L. Pangione; F. Parra; A. Patel; W. Peebles; R. Perez; S. Pinches; L. Piron; M. Price; M. Reinke; P. Ricci; F. Riva; C. Roach; M. Romanelli; D. Ryan; S. Saarelma; A. Saveliev; R. Scannell; A. Schekochihin; S. Sharapov; R. Sharples; V. Shevchenko; K. Shinohara; S. Silburn; J. Simpson; A. Stanier; J. Storrs; H. Summers; Y. Takase; P. Tamain; H. Tanabe; H. Tanaka; K. Tani; D. Taylor; D. Thomas; N. Thomas-Davies; A. Thornton; M. Turnyanskiy; M. Valovic; R. Vann; F. Van Wyk; N. Walkden; T. Watanabe; H. Wilson; M. Wischmeier; T. Yamada; J. Young; S. Zoletnik

doi:10.1109/TPS.2025.3583419

An Open Data Service for Supporting Research in Machine Learning on Tokamak Data

Samuel Jackson, Saiful Khan, Nathan Cummings, James Hodson, Shaun De Witt, Stanislas Pamela, Rob Akers, Jeyan Thiyagalingam, A. Kirk, J. Adamek, R. J. Akers, S. Allan, L. Appel, F. Arese Lucini, M. Barnes, T. Barrett, N. Ben Ayed, W. Boeglin, J. Bradley, P. K. BrowningJ. Brunner, P. Cahyna, S. Cardnell, M. Carr, F. Casson, M. Cecconello, C. Challis, I. T. Chapman, S. Chapman, J. Chorley, S. Conroy, N. Conway, W. A. Cooper, M. Cox, N. Crocker, B. Crowley, G. Cunningham, A. Danilov, D. Darrow, R. Dendy, D. Dickinson, W. Dorland, B. Dudson, D. Dunai, L. Easy, S. Elmore, M. Evans, T. Farley, N. Fedorczak, A. Field, G. Fishpool, I. Fitzgerald, M. Fox, S. Freethy, L. Garzotti, Y. C. Ghim, K. Gi, K. Gibson, M. Gorelenkova, W. Gracias, C. Gurl, W. Guttenfelder, C. Ham, J. Harrison, D. Harting, E. Havlickova, N. Hawkes, T. Hender, S. Henderson, E. Highcock, J. Hillesheim, B. Hnat, J. Horacek, J. Howard, D. Howell, B. Huang, K. Imada, M. Inomoto, R. Imazawa, O. Jones, K. Kadowaki, S. Kaye, D. Keeling, I. Klimek, M. Kocan, L. Kogan, M. Komm, W. Lai, J. Leddy, H. Leggate, J. Hollocombe, B. Lipschultz, S. Lisgo, Y. Q. Liu, B. Lloyd, B. Lomanowski, V. Lukin, I. Lupelli, G. Maddison, J. Madsen, J. Mailloux, R. Martin, G. McArdle, K. McClements, B. McMillan, A. Meakins, H. Meyer, C. Michael, F. Militello, J. Milnes, A. W. Morris, G. Motojima, D. Muir, G. Naylor, A. Nielsen, M. O'Brien, T. O'Gorman, M. O'Mullane, J. Olsen, J. Omotani, Y. Ono, S. Pamela, L. Pangione, F. Parra, A. Patel, W. Peebles, R. Perez, S. Pinches, L. Piron, M. Price, M. Reinke, P. Ricci, F. Riva, C. Roach, M. Romanelli, D. Ryan, S. Saarelma, A. Saveliev, R. Scannell, A. Schekochihin, S. Sharapov, R. Sharples, V. Shevchenko, K. Shinohara, S. Silburn, J. Simpson, A. Stanier, J. Storrs, H. Summers, Y. Takase, P. Tamain, H. Tanabe, H. Tanaka, K. Tani, D. Taylor, D. Thomas, N. Thomas-Davies, A. Thornton, M. Turnyanskiy, M. Valovic, R. Vann, F. Van Wyk, N. Walkden, T. Watanabe, H. Wilson, M. Wischmeier, T. Yamada, J. Young, S. Zoletnik

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

The increasing complexity and volume of plasma fusion experimental data, coupled with the growing adoption of machine learning in fusion research, necessitate advanced and efficient data management solutions. We propose an open data service for fusion experiments operated by the UKAEA, designed to address the evolving needs of machine-learning-driven fusion research. Our system provides a framework to organize MAST, MAST upgrade (MAST-U), and Joint European Torus (JET) experimental data in accordance with findability, accessibility, interoperability, and reuse (FAIR) principles, using distributed object storage for scalability and a relational database for efficient metadata indexing. In addition, it offers simplified abstractions through an application programming interface (API), facilitating seamless data access and integration with data analysis and machine learning workflows. Performance evaluation of metrics such as data load time and throughput, across varying numbers of parallel workers, demonstrates the data pipeline's optimization for efficient machine learning application development. Our solution significantly enhances support for data-driven research and machine learning applications in fusion by laying the groundwork for open, FAIR-compliant fusion data, which enables cross-machine analysis, prompts international collaboration, and potentially accelerates advancements in fusion energy research.

Original language	English (US)
Journal	IEEE Transactions on Plasma Science
DOIs	https://doi.org/10.1109/TPS.2025.3583419
State	Accepted/In press - 2025

All Science Journal Classification (ASJC) codes

Nuclear and High Energy Physics
Condensed Matter Physics

Keywords

Fusion data
scientific data management
web service application programming interface (API)

Access to Document

10.1109/TPS.2025.3583419

Cite this

Jackson, S., Khan, S., Cummings, N., Hodson, J., De Witt, S., Pamela, S., Akers, R., Thiyagalingam, J., Kirk, A., Adamek, J., Akers, R. J., Allan, S., Appel, L., Arese Lucini, F., Barnes, M., Barrett, T., Ben Ayed, N., Boeglin, W., Bradley, J., ... Zoletnik, S. (Accepted/In press). An Open Data Service for Supporting Research in Machine Learning on Tokamak Data. IEEE Transactions on Plasma Science. https://doi.org/10.1109/TPS.2025.3583419

@article{1c4982b896164fea8b7aa2c4af611cc5,

title = "An Open Data Service for Supporting Research in Machine Learning on Tokamak Data",

abstract = "The increasing complexity and volume of plasma fusion experimental data, coupled with the growing adoption of machine learning in fusion research, necessitate advanced and efficient data management solutions. We propose an open data service for fusion experiments operated by the UKAEA, designed to address the evolving needs of machine-learning-driven fusion research. Our system provides a framework to organize MAST, MAST upgrade (MAST-U), and Joint European Torus (JET) experimental data in accordance with findability, accessibility, interoperability, and reuse (FAIR) principles, using distributed object storage for scalability and a relational database for efficient metadata indexing. In addition, it offers simplified abstractions through an application programming interface (API), facilitating seamless data access and integration with data analysis and machine learning workflows. Performance evaluation of metrics such as data load time and throughput, across varying numbers of parallel workers, demonstrates the data pipeline's optimization for efficient machine learning application development. Our solution significantly enhances support for data-driven research and machine learning applications in fusion by laying the groundwork for open, FAIR-compliant fusion data, which enables cross-machine analysis, prompts international collaboration, and potentially accelerates advancements in fusion energy research.",

keywords = "Fusion data, scientific data management, web service application programming interface (API)",

author = "Samuel Jackson and Saiful Khan and Nathan Cummings and James Hodson and \{De Witt\}, Shaun and Stanislas Pamela and Rob Akers and Jeyan Thiyagalingam and A. Kirk and J. Adamek and Akers, \{R. J.\} and S. Allan and L. Appel and \{Arese Lucini\}, F. and M. Barnes and T. Barrett and \{Ben Ayed\}, N. and W. Boeglin and J. Bradley and Browning, \{P. K.\} and J. Brunner and P. Cahyna and S. Cardnell and M. Carr and F. Casson and M. Cecconello and C. Challis and Chapman, \{I. T.\} and S. Chapman and J. Chorley and S. Conroy and N. Conway and Cooper, \{W. A.\} and M. Cox and N. Crocker and B. Crowley and G. Cunningham and A. Danilov and D. Darrow and R. Dendy and D. Dickinson and W. Dorland and B. Dudson and D. Dunai and L. Easy and S. Elmore and M. Evans and T. Farley and N. Fedorczak and A. Field and G. Fishpool and I. Fitzgerald and M. Fox and S. Freethy and L. Garzotti and Ghim, \{Y. C.\} and K. Gi and K. Gibson and M. Gorelenkova and W. Gracias and C. Gurl and W. Guttenfelder and C. Ham and J. Harrison and D. Harting and E. Havlickova and N. Hawkes and T. Hender and S. Henderson and E. Highcock and J. Hillesheim and B. Hnat and J. Horacek and J. Howard and D. Howell and B. Huang and K. Imada and M. Inomoto and R. Imazawa and O. Jones and K. Kadowaki and S. Kaye and D. Keeling and I. Klimek and M. Kocan and L. Kogan and M. Komm and W. Lai and J. Leddy and H. Leggate and J. Hollocombe and B. Lipschultz and S. Lisgo and Liu, \{Y. Q.\} and B. Lloyd and B. Lomanowski and V. Lukin and I. Lupelli and G. Maddison and J. Madsen and J. Mailloux and R. Martin and G. McArdle and K. McClements and B. McMillan and A. Meakins and H. Meyer and C. Michael and F. Militello and J. Milnes and Morris, \{A. W.\} and G. Motojima and D. Muir and G. Naylor and A. Nielsen and M. O'Brien and T. O'Gorman and M. O'Mullane and J. Olsen and J. Omotani and Y. Ono and S. Pamela and L. Pangione and F. Parra and A. Patel and W. Peebles and R. Perez and S. Pinches and L. Piron and M. Price and M. Reinke and P. Ricci and F. Riva and C. Roach and M. Romanelli and D. Ryan and S. Saarelma and A. Saveliev and R. Scannell and A. Schekochihin and S. Sharapov and R. Sharples and V. Shevchenko and K. Shinohara and S. Silburn and J. Simpson and A. Stanier and J. Storrs and H. Summers and Y. Takase and P. Tamain and H. Tanabe and H. Tanaka and K. Tani and D. Taylor and D. Thomas and N. Thomas-Davies and A. Thornton and M. Turnyanskiy and M. Valovic and R. Vann and \{Van Wyk\}, F. and N. Walkden and T. Watanabe and H. Wilson and M. Wischmeier and T. Yamada and J. Young and S. Zoletnik",

note = "Publisher Copyright: {\textcopyright} IEEE. 1973-2012 IEEE.",

year = "2025",

doi = "10.1109/TPS.2025.3583419",

language = "English (US)",

journal = "IEEE Transactions on Plasma Science",

issn = "0093-3813",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

Jackson, S, Khan, S, Cummings, N, Hodson, J, De Witt, S, Pamela, S, Akers, R, Thiyagalingam, J, Kirk, A, Adamek, J, Akers, RJ, Allan, S, Appel, L, Arese Lucini, F, Barnes, M, Barrett, T, Ben Ayed, N, Boeglin, W, Bradley, J, Browning, PK, Brunner, J, Cahyna, P, Cardnell, S, Carr, M, Casson, F, Cecconello, M, Challis, C, Chapman, IT, Chapman, S, Chorley, J, Conroy, S, Conway, N, Cooper, WA, Cox, M, Crocker, N, Crowley, B, Cunningham, G, Danilov, A, Darrow, D, Dendy, R, Dickinson, D, Dorland, W, Dudson, B, Dunai, D, Easy, L, Elmore, S, Evans, M, Farley, T, Fedorczak, N, Field, A, Fishpool, G, Fitzgerald, I, Fox, M, Freethy, S, Garzotti, L, Ghim, YC, Gi, K, Gibson, K, Gorelenkova, M, Gracias, W, Gurl, C, Guttenfelder, W, Ham, C, Harrison, J, Harting, D, Havlickova, E, Hawkes, N, Hender, T, Henderson, S, Highcock, E, Hillesheim, J, Hnat, B, Horacek, J, Howard, J, Howell, D, Huang, B, Imada, K, Inomoto, M, Imazawa, R, Jones, O, Kadowaki, K, Kaye, S, Keeling, D, Klimek, I, Kocan, M, Kogan, L, Komm, M, Lai, W, Leddy, J, Leggate, H, Hollocombe, J, Lipschultz, B, Lisgo, S, Liu, YQ, Lloyd, B, Lomanowski, B, Lukin, V, Lupelli, I, Maddison, G, Madsen, J, Mailloux, J, Martin, R, McArdle, G, McClements, K, McMillan, B, Meakins, A, Meyer, H, Michael, C, Militello, F, Milnes, J, Morris, AW, Motojima, G, Muir, D, Naylor, G, Nielsen, A, O'Brien, M, O'Gorman, T, O'Mullane, M, Olsen, J, Omotani, J, Ono, Y, Pamela, S, Pangione, L, Parra, F, Patel, A, Peebles, W, Perez, R, Pinches, S, Piron, L, Price, M, Reinke, M, Ricci, P, Riva, F, Roach, C, Romanelli, M, Ryan, D, Saarelma, S, Saveliev, A, Scannell, R, Schekochihin, A, Sharapov, S, Sharples, R, Shevchenko, V, Shinohara, K, Silburn, S, Simpson, J, Stanier, A, Storrs, J, Summers, H, Takase, Y, Tamain, P, Tanabe, H, Tanaka, H, Tani, K, Taylor, D, Thomas, D, Thomas-Davies, N, Thornton, A, Turnyanskiy, M, Valovic, M, Vann, R, Van Wyk, F, Walkden, N, Watanabe, T, Wilson, H, Wischmeier, M, Yamada, T, Young, J & Zoletnik, S 2025, 'An Open Data Service for Supporting Research in Machine Learning on Tokamak Data', IEEE Transactions on Plasma Science. https://doi.org/10.1109/TPS.2025.3583419

TY - JOUR

T1 - An Open Data Service for Supporting Research in Machine Learning on Tokamak Data

AU - Jackson, Samuel

AU - Khan, Saiful

AU - Cummings, Nathan

AU - Hodson, James

AU - De Witt, Shaun

AU - Pamela, Stanislas

AU - Akers, Rob

AU - Thiyagalingam, Jeyan

AU - Kirk, A.

AU - Adamek, J.

AU - Akers, R. J.

AU - Allan, S.

AU - Appel, L.

AU - Arese Lucini, F.

AU - Barnes, M.

AU - Barrett, T.

AU - Ben Ayed, N.

AU - Boeglin, W.

AU - Bradley, J.

AU - Browning, P. K.

AU - Brunner, J.

AU - Cahyna, P.

AU - Cardnell, S.

AU - Carr, M.

AU - Casson, F.

AU - Cecconello, M.

AU - Challis, C.

AU - Chapman, I. T.

AU - Chapman, S.

AU - Chorley, J.

AU - Conroy, S.

AU - Conway, N.

AU - Cooper, W. A.

AU - Cox, M.

AU - Crocker, N.

AU - Crowley, B.

AU - Cunningham, G.

AU - Danilov, A.

AU - Darrow, D.

AU - Dendy, R.

AU - Dickinson, D.

AU - Dorland, W.

AU - Dudson, B.

AU - Dunai, D.

AU - Easy, L.

AU - Elmore, S.

AU - Evans, M.

AU - Farley, T.

AU - Fedorczak, N.

AU - Field, A.

AU - Fishpool, G.

AU - Fitzgerald, I.

AU - Fox, M.

AU - Freethy, S.

AU - Garzotti, L.

AU - Ghim, Y. C.

AU - Gi, K.

AU - Gibson, K.

AU - Gorelenkova, M.

AU - Gracias, W.

AU - Gurl, C.

AU - Guttenfelder, W.

AU - Ham, C.

AU - Harrison, J.

AU - Harting, D.

AU - Havlickova, E.

AU - Hawkes, N.

AU - Hender, T.

AU - Henderson, S.

AU - Highcock, E.

AU - Hillesheim, J.

AU - Hnat, B.

AU - Horacek, J.

AU - Howard, J.

AU - Howell, D.

AU - Huang, B.

AU - Imada, K.

AU - Inomoto, M.

AU - Imazawa, R.

AU - Jones, O.

AU - Kadowaki, K.

AU - Kaye, S.

AU - Keeling, D.

AU - Klimek, I.

AU - Kocan, M.

AU - Kogan, L.

AU - Komm, M.

AU - Lai, W.

AU - Leddy, J.

AU - Leggate, H.

AU - Hollocombe, J.

AU - Lipschultz, B.

AU - Lisgo, S.

AU - Liu, Y. Q.

AU - Lloyd, B.

AU - Lomanowski, B.

AU - Lukin, V.

AU - Lupelli, I.

AU - Maddison, G.

AU - Madsen, J.

AU - Mailloux, J.

AU - Martin, R.

AU - McArdle, G.

AU - McClements, K.

AU - McMillan, B.

AU - Meakins, A.

AU - Meyer, H.

AU - Michael, C.

AU - Militello, F.

AU - Milnes, J.

AU - Morris, A. W.

AU - Motojima, G.

AU - Muir, D.

AU - Naylor, G.

AU - Nielsen, A.

AU - O'Brien, M.

AU - O'Gorman, T.

AU - O'Mullane, M.

AU - Olsen, J.

AU - Omotani, J.

AU - Ono, Y.

AU - Pamela, S.

AU - Pangione, L.

AU - Parra, F.

AU - Patel, A.

AU - Peebles, W.

AU - Perez, R.

AU - Pinches, S.

AU - Piron, L.

AU - Price, M.

AU - Reinke, M.

AU - Ricci, P.

AU - Riva, F.

AU - Roach, C.

AU - Romanelli, M.

AU - Ryan, D.

AU - Saarelma, S.

AU - Saveliev, A.

AU - Scannell, R.

AU - Schekochihin, A.

AU - Sharapov, S.

AU - Sharples, R.

AU - Shevchenko, V.

AU - Shinohara, K.

AU - Silburn, S.

AU - Simpson, J.

AU - Stanier, A.

AU - Storrs, J.

AU - Summers, H.

AU - Takase, Y.

AU - Tamain, P.

AU - Tanabe, H.

AU - Tanaka, H.

AU - Tani, K.

AU - Taylor, D.

AU - Thomas, D.

AU - Thomas-Davies, N.

AU - Thornton, A.

AU - Turnyanskiy, M.

AU - Valovic, M.

AU - Vann, R.

AU - Van Wyk, F.

AU - Walkden, N.

AU - Watanabe, T.

AU - Wilson, H.

AU - Wischmeier, M.

AU - Yamada, T.

AU - Young, J.

AU - Zoletnik, S.

PY - 2025

Y1 - 2025

N2 - The increasing complexity and volume of plasma fusion experimental data, coupled with the growing adoption of machine learning in fusion research, necessitate advanced and efficient data management solutions. We propose an open data service for fusion experiments operated by the UKAEA, designed to address the evolving needs of machine-learning-driven fusion research. Our system provides a framework to organize MAST, MAST upgrade (MAST-U), and Joint European Torus (JET) experimental data in accordance with findability, accessibility, interoperability, and reuse (FAIR) principles, using distributed object storage for scalability and a relational database for efficient metadata indexing. In addition, it offers simplified abstractions through an application programming interface (API), facilitating seamless data access and integration with data analysis and machine learning workflows. Performance evaluation of metrics such as data load time and throughput, across varying numbers of parallel workers, demonstrates the data pipeline's optimization for efficient machine learning application development. Our solution significantly enhances support for data-driven research and machine learning applications in fusion by laying the groundwork for open, FAIR-compliant fusion data, which enables cross-machine analysis, prompts international collaboration, and potentially accelerates advancements in fusion energy research.

AB - The increasing complexity and volume of plasma fusion experimental data, coupled with the growing adoption of machine learning in fusion research, necessitate advanced and efficient data management solutions. We propose an open data service for fusion experiments operated by the UKAEA, designed to address the evolving needs of machine-learning-driven fusion research. Our system provides a framework to organize MAST, MAST upgrade (MAST-U), and Joint European Torus (JET) experimental data in accordance with findability, accessibility, interoperability, and reuse (FAIR) principles, using distributed object storage for scalability and a relational database for efficient metadata indexing. In addition, it offers simplified abstractions through an application programming interface (API), facilitating seamless data access and integration with data analysis and machine learning workflows. Performance evaluation of metrics such as data load time and throughput, across varying numbers of parallel workers, demonstrates the data pipeline's optimization for efficient machine learning application development. Our solution significantly enhances support for data-driven research and machine learning applications in fusion by laying the groundwork for open, FAIR-compliant fusion data, which enables cross-machine analysis, prompts international collaboration, and potentially accelerates advancements in fusion energy research.

KW - Fusion data

KW - scientific data management

KW - web service application programming interface (API)

UR - https://www.scopus.com/pages/publications/105013784179

UR - https://www.scopus.com/inward/citedby.url?scp=105013784179&partnerID=8YFLogxK

U2 - 10.1109/TPS.2025.3583419

DO - 10.1109/TPS.2025.3583419

M3 - Article

AN - SCOPUS:105013784179

SN - 0093-3813

JO - IEEE Transactions on Plasma Science

JF - IEEE Transactions on Plasma Science

ER -

An Open Data Service for Supporting Research in Machine Learning on Tokamak Data

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