doi : 

Authors : Rushil Anirudh, Rick Archibald, M. Salman Asif, Markus M. Becker, Sadruddin Benkadda, Peer-Timo Bremer, Rick H.S. Budé, C.S. Chang, Lei Chen, R. M. Churchill, Jonathan Citrin, Jim A Gaffney, Ana Gainaru, Walter Gekelman, Tom Gibbs, Satoshi Hamaguchi, Christian Hill, Kelli Humbird, Sören Jalas, Satoru Kawaguchi, Gon-Ho Kim, Manuel Kirchen, Scott Klasky, John L. Kline, Karl Krushelnick, Bogdan Kustowski, Giovanni Lapenta, Wenting Li, Tammy Ma, Nigel J. Mason, Ali Mesbah, Craig Michoski, Todd Munson, Izumi Murakami, Habib N. Najm, K. Erik J. Olofsson, Seolhye Park, J. Luc Peterson, Michael Probst, Dave Pugmire, Brian Sammuli, Kapil Sawlani, Alexander Scheinker, David P. Schissel, Rob J. Shalloo, Jun Shinagawa, Jaegu Seong, Brian K. Spears, Jonathan Tennyson, Jayaraman Thiagarajan, Catalin M. Ticoş, Jan Trieschmann, Jan van Dijk, Brian Van Essen, Peter Ventzek, Haimin Wang, Jason T. L. Wang, Zhehui Wang, Kristian Wende, Xueqiao Xu, Hiroshi Yamada, Tatsuya Yokoyama, Xinhua Zhang

Abstract : 

Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS). A large amount of data and machine learning algorithms go hand in hand. Most plasma data, whether experimental, observational or computational, are generated or collected by machines today. It is now becoming impractical for humans to analyze all the data manually. Therefore, it is imperative to train machines to analyze and interpret (eventually) such data as intelligently as humans but far more efficiently in quantity. Despite the recent impressive progress in applications of data science to plasma science and technology, the emerging field of DDPS is still in its infancy. Fueled by some of the most challenging problems such as fusion energy, plasma processing of materials, and fundamental understanding of the universe through observable plasma phenomena, it is expected that DDPS continues to benefit significantly from the interdisciplinary marriage between plasma science and data science into the foreseeable future.