  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.
