Data-Driven Discovery Science in Chemistry (D3SC)

The amount and variety of data generated in the chemical sciences, and the rate at which it is being produced, are rapidly increasing, so there is a need for corresponding growth in our ability to extract useful insight from interrelated sources. A similar need is recognized across the National Science Foundation (NSF). One example is the `Harnessing the Data Revolution` component in the recently-released document, 10 Big Ideas for Future NSF Investment, which sets the goal of developing `a cohesive, national-scale approach to research data infrastructure and a 21st-century workforce capable of working effectively with data`.1 This creates an opportunity to enable the chemistry community to effectively share, mine, and repurpose its rapidly-growing chemical datasets and to apply state-of-the-art data analytics tools to expand chemical understanding.

Through this Dear Colleague Letter (DCL), the Division of Chemistry (CHE) invites submission of requests for supplements and EAGER (EArly-concept Grants for Exploratory Research) and RAISE (Research Advanced by Interdisciplinary Science and Engineering)2 proposals that seek to capitalize on the data revolution. Successful proposals will emphasize what new information can be obtained from better utilization of data (including data from multiple laboratories, techniques, and/or chemical systems), and how this can lead to new research directions. Proposals that foster and strengthen interactions among chemists — particularly experimentalists and data scientists — to advance research goals, are strongly encouraged. Examples of possible projects include (but are not limited to) using tools of data visualization, data mining, machine learning, or other data analytics to:

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