Mining Science Data
Chandrika Kamath
Lawrence Livermore National Laboratory
The data from scientific simulations, observations, and experiments
is now being measured in terabytes and will soon reach the petabyte
regime. The size of the data, as well as its complexity, make it
difficult to find useful information in the data. This is of course
disconcerting to scientists who wonder about the science still
undiscovered in the data. The Sapphire scientific data mining project
at Lawrence Livermore National Laboratory [www.llnl.gov/casc/sapphire]
has been addressing this concern by applying data mining techniques
to problems ranging in size from a few megabytes to a hundred terabytes
in a variety of domains. In this poster, I will describe how we are
using data mining techniques to separate signals in climate simulations,
identify key features for edge-harmonic oscillations, classify orbits
in a Poincare plot, and track features of interest in experimental images.