Making MAST fusion tokamak data open and FAIR | Nathan Cummings, UK Atomic Energy Authority
0The fusion community has historically operated within silos. Sharing data, when it does occur, tends to be ad-hoc, in non-standard formats, with little resources available for carefully curated provenance descriptions. For an open fusion database, we as a community need to develop a shared ontology for describing our data, resulting in interoperable datasets, which can enable a new generation of fusion researchers to apply modern AI/ML methods on larger sets of data than ever before to deepen our understanding of magnetic confinement fusion (MCF) and tokamak operation.\n\nIn recent years, the fusion community has begun to take this challenge seriously. From the development of the IMAS (ITER Integrated Modelling and Analysis Suite) Data Dictionary, intended to be applicable to fusion data from a wide range of devices, to more strategic assessments of the current landscape and demonstrator technology from the FAIR4fusion project, and now with the IAEA CRP on AI for Fusion, the need for a better way of accessing and working with data to accelerate fusion R&D is firmly on the agenda.\n\nThe UK Atomic Energy Authority (UKAEA) intends to lead this effort by developing an open data access platform for data from their Mega-Ampere Spherical Tokamak (MAST) that conforms to FAIR principles (Findable, Accessible, Interoperable, Reusable), as an exemplar for other fusion experiments, and alongside the objectives of the IAEA AI for Fusion coordinated research project. Some use cases that such a database could enable are outlined, along with a discussion about the various decisions and challenges that need to be overcome as this effort progresses. This includes deciding on how to adapt to a common standard for data, where to store the data, how to update it, and crucially, how modern technology stacks will enable scalable, performant access to data.\n\nA number of examples in other scientific fields will be discussed, outlining their merits and limitations with regard to the previously mentioned use cases, and how this is informing the development of an open and FAIR fusion database for MAST data.\n\nSpeakers:\nNathan Cummings\nUK Atomic Energy Authority\n\nModerators:\nDiakhère Gueye\nInternational Atomic Energy Agency (IAEA)\n\nIn Partnership with: International Atomic Energy Agency @IAEAvideo \n\nJoin the Neural Network! \nhttps://aiforgood.itu.int/neural-network/\nThe AI for Good networking community platform powered by AI. \nDesigned to help users build connections with innovators and experts, link innovative ideas with social impact opportunities, and bring the community together to advance the SDGs using AI.\n\n Watch the latest #AIforGood videos!\n\n\nExplore more #AIforGood content:\n AI for Good Top Hits\n • Top Hits \n\n AI for Good Webinars\n • AI for Good Webinars \n\n AI for Good Keynotes\n • AI for Good Keynotes \n\n Stay updated and join our weekly AI for Good newsletter:\nhttp://eepurl.com/gI2kJ5\n\n Discover what's next on our programme!\nhttps://aiforgood.itu.int/programme/\n\nCheck out the latest AI for Good news:\nhttps://aiforgood.itu.int/newsroom/\n\nExplore the AI for Good blog:\nhttps://aiforgood.itu.int/ai-for-good-blog/\n\n Connect on our social media:\nWebsite: https://aiforgood.itu.int/\nTwitter: https://twitter.com/AIforGood\nLinkedIn Page: https://www.linkedin.com/company/26511907 \nLinkedIn Group: https://www.linkedin.com/groups/8567748 \nInstagram: https://www.instagram.com/aiforgood \nFacebook: https://www.facebook.com/AIforGood\n\nWhat is AI for Good?\nWe have less than 10 years to solve the UN SDGs and AI holds great promise to advance many of the sustainable development goals and targets.\nMore than a Summit, more than a movement, AI for Good is presented as a year round digital platform where AI innovators and problem owners learn, build and connect to help identify practical AI solutions to advance the United Nations Sustainable Development Goals.\nAI for Good is organized by ITU in partnership with 40 UN Sister Agencies and co-convened with Switzerland.\n\nDisclaimer:\nThe views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.