Workshop: Framing the Role of Big Data and Modern Data Science in Chemistry

化学部的这一奖项支持2017年4月18日至19日在弗吉尼亚州阿灵顿举行的“CHE研讨会：构建大数据和现代数据科学在化学中的作用”。教授纽约州立大学布法罗、范德比尔特和爱荷华州州立大学的Johannes Hachmann、John姆克林和Theresa Windus分别组建了一个团队，以解决大数据研究和现代数据科学在化学领域的潜力。该研讨会汇集了大约45名化学科学领域的领导者，他们在该领域的发展方面具有专业知识。本次研讨会的目标是就数据驱动研究以及实现数据驱动研究的工具展开广泛讨论。研讨会的长期目标是塑造这一新兴领域，并帮助开创化学发现过程的根本变革。这些目标与“关于化学中数据驱动的发现科学的亲爱的同事信”（D3 SC），NSF 17-036中表达的想法和需求非常一致，这反映了“利用数据革命”的需求，被认为是“未来NSF投资的十大想法”之一。大数据和现代数据科学的应用创造了新的工具，有望改变化学的发现和设计过程，从而提高我们的创新能力。除了深远的技术影响外，这一发展还有望大大增加公共和私人投资在资源和时间方面的回报。

This award from the Division of Chemistry supports "CHE Workshop: Framing the Role of Big Data and Modern Data Science in Chemistry", held April 18-19, 2017 in Arlington, Virginia. Profs. Johannes Hachmann, John McLean, and Theresa Windus of SUNY Buffalo, Vanderbilt and Iowa State University respectively, have assembled a team to address the potential of big data research and modern data science in the field of chemistry. The workshop brings together a diverse group of approximately 45 leaders in the chemical sciences who have expertise in the development of this field. The goals of the workshop are to spearhead a broad discussion about data-driven research, and the tools to enable it. The long-term objectives of the workshop are to shape this emerging field, and to help pioneer a fundamental transformation of the discovery process in chemistry. These goals are well aligned with ideas and needs expressed in the Dear Colleague Letter on Data-Driven Discovery Science in Chemistry (D3SC), NSF 17-036, which is reflective of the "Harnessing the Data Revolution" need, recognized as one of the "10 Big Ideas for Future NSF Investment". The application of big data and modern data science creates new tools that promise to transform the discovery and design process in chemistry and thus boost our capacity for innovation. In addition to the far-reaching technological implications, this development also promises a significant increase in the return on public and private investments, both in terms of resources and time.