  The prediction of solar flares, eruptions, and high energy particle storms is
of great societal importance. The data mining approach to forecasting has been
shown to be very promising. Benchmark datasets are a key element in the further
development of data-driven forecasting. With one or more benchmark data sets
established, judicious use of both the data themselves and the selection of
prediction algorithms is key to developing a high quality and robust method for
the prediction of geo-effective solar activity. We review here briefly the
process of generating benchmark datasets and developing prediction algorithms.
