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PlasmaFAIR: Improving the Sustainability of Software in Plasma Science

Authors: Pattinson, Liam; Hill, Peter;

PlasmaFAIR: Improving the Sustainability of Software in Plasma Science

Abstract

The PlasmaFAIR project provides free software support to researchers at all career stages within the plasma science community. Our ethos is centred on the FAIR principles[1], which state that data and software should be Findable, Accessible, Interoperable, and Reusable. We aim to improve the ease-of-use, robustness and sustainability of plasma software by reviewing projects and making recommendations via our software ‘health checks’ and by working alongside scientists to provide direct software engineering support. Our projects often include the addition of testing and documentation frameworks, the implementation of automation techniques, and the packaging of software for wider distribution. We also provide longer-term support for some projects. One example is Pyrokinetics[2], which acts as a translation layer between multiple plasma physics simulation codes to enable easier cross-code comparisons and parameter scans. Following work to redesign and simplify some of its core procedures, Pyrokinetics has rapidly become a community tool supported across multiple institutions. Similarly, our work on Scotty[3], a synthetic diagnostic for plasma experiments developed as a PhD project at the University of York and the Culham Centre for Fusion Energy, has resulted in fully-fledged research software with an international user base spanning from Singapore to San Diego. Beyond our work supporting plasma physics software projects, we also contribute to open-source community tools such as netCDF and FAIRDataPipeline[4], and we develop new tools where the need arises. More information is available at https://plasmafair.github.io. [1] https://doi.org/10.1038/sdata.2016.18 [2] https://doi.org/10.5281/zenodo.10276528 [3] https://doi.org/10.1088/1361-6587/ac57a1 [4] https://www.fairdatapipeline.org A recording of this session is available on YouTube: https://youtu.be/MjhhCI0GOU8

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green