Computational and Data-Enabled Science and Engineering

Large-scale simulations and the ability to accumulate massive amounts of data have revolutionized science and engineering. The goal of the Computational and Data-enabled Science and Engineering (CDS&E) meta-program is to identify and capitalize on opportunities for major scientific and engineering breakthroughs through new computational and data-analysis approaches and best practices. The CDS&E meta-program supports projects that harness computation and data to advance knowledge and accelerate discovery above and beyond the goals of the participating individual programs. The intellectual drivers may be in an individual discipline or cut across more than one discipline in various Divisions and Directorates. A CDS&E proposal should enable and/or utilize the development and adaptation of advances in research and infrastructure in computational and data science.

The CDS&E meta-program encourages research that pushes the envelope of science and engineering through computation and data, welcoming proposals in any research area supported by the participating divisions. A proposal may address topics that develop or enable interactions among theory, computing, experiment, and observation to achieve progress on hitherto intractable science and engineering problems. Areas of emphasis for CDS&E vary by program. PIs are advised to consult the "related programs" links below before submitting.

The CDS&E meta-program is not intended to replace existing programs that support projects involving computation or the analysis of large or complex data sets using established methods. Rather, proposals submitted to the CDS&E meta-program must have a significant component of computational or data science that goes well beyond what would typically be included in these programs.Any proposal submitted to the CDS&E program that is not responsive to this Program Description may be transferred to or reviewed within the context of an individual program. A proposal requesting consideration withi