Workshop on Data-Enabled Science

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The Mathematical and Physical Sciences (MPS) community generates much of the data in science. Major experiments and facilities are now generating petabytes of data per year that must be distributed globally for analysis. Projects already in development will generate much largervolumes at faster rates, approaching an exabyte per week, with exaflop computing capacity needed to perform the analysis. In addition to this growing number of prodigious data generators, virtually all of science is becoming data-intensive, with increasing size and/or complexity, even at the level of PIs in individual labs. This trend extends beyond MPS disciplines to:biological data; financial, commercial, and retail data; audio and visual data; data assimilation and data fusion; and data in the humanities and social sciences. Virtually all disciplines need potentially radical new mathematical and statistical ways to handle future data sets if scientific advances are to be realized. The proposed MPS Workshop on Data-Enabled Science will provide a high-level assessment of the needs of the MPS communities, including anticipated data generation, capability and inability to mine the data for science, strengths and weaknesses of current efforts, and work on developing new algorithms and mathematical approaches. The workshop will also provide an assessment of the resource requirements for addressing these needs over the next five years.