Spokes: MEDIUM: NORTHEAST: Collaborative: Advancing a Data-Driven Discovery and Rational Design Paradigm in Chemistry

在数学和物理科学局(MPS)的化学司(CHE)和材料研究司(DMR)以及计算机与信息科学与工程局(CEISE)的支持下，该项目旨在促进现代数据科学在化学中的应用。特别是，该项目将促进在分子科学中使用机器学习和其他数据挖掘技术，并促进和联合利益攸关方社区，从而推动数据驱动的化学研究领域。该项目及其所代表的社区的工作旨在改变化学解决具有挑战性的发现和设计问题的能力。这种方法可以极大地加速和简化导致化学创新的过程--这是经济和技术进步的一个重要因素--从而提高公共和私人投资的回报。该项目还解决了化学领域所需的培训和劳动力发展的相应问题，从而确保了美国的国际竞争力。该项目的使命是确立大数据研究在化学领域的作用，即促进、启用和推进数据驱动的发现和合理设计的思想。该项目旨在制定一个由社区驱动的路线图，并促进具体的解决办法，这些解决办法超出了个别利益攸关方的分散努力的范围。大数据中心和Spokes生态系统是实现这一愿景并加快这一高度优先研究领域进展的理想框架。手头的工作旨在实施最近NSF化学司关于制定大数据和现代数据科学在化学中的作用的研讨会的一些重要发现。该演讲项目的四个标志性举措包括(I)规划、协调、整合和巩固社区开发的用于化学大数据研究的软件工具，以及制定指导方针、最佳做法和标准；(Ii)组织社区建设研讨会，将寻求解决方案的人与解决方案提供者联系起来，并解决从战略到技术的各种问题；以及(Iii)创建和传播社区开发的教材，以及为教育和劳动力发展制定课程、计划和课程建议，以反映化学研究中不断变化的、以数据为中心的方法；(Iv)为社区数据集提供对共享硬件基础设施的访问，现场数据挖掘能力，以及对特定领域方法和硬件问题的探索。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

With support from the Division of Chemistry (CHE) and the Division of Materials Research (DMR) in the Directorate for Mathematical and Physical Sciences (MPS) and the Directorate for Computer & Information Science & Engineering (CISE), this project aims to advance the use of modern data science in chemistry. In particular, the project will advance the field of data-driven chemical research by promoting the use of machine learning and other data mining techniques in the molecular sciences and by fostering and coalescing a community of stakeholders. The work of the project and the community it represents aims to transform chemistry's ability to tackle challenging discovery and design problems. This approach can dramatically accelerate and streamline the process that leads to chemical innovation -- an important factor in economic and technological advancement -- and thus result in an improved return on public and private investments. The project also addresses corresponding questions of training and workforce development needed in chemistry, thus insuring the US's international competitiveness. The mission of this project is to assert the role of big data research in the chemical domain, i.e., to promote, enable, and advance the ideas of data-driven discovery and rational design. The project aims to create a community-driven roadmap as well as facilitate concrete solutions that are beyond the scope of the disjointed efforts of its individual stakeholders. The Big Data Hubs and Spokes ecosystem is the ideal framework to realizing this vision and accelerating progress in this high-priority area of research. The effort at hand sets out to implement some of the key findings of the recent NSF Division of Chemistry workshop on Framing the Role of Big Data and Modern Data Science in Chemistry. The four signature initiatives of this Spoke project include (i) the planning, coordination, integration, and consolidation of community-developed software tools for big data research in chemistry as well as the formulation of guidelines, best practices, and standards; (ii) the organization of workshops for community building, to connect solution seekers with solution providers, and to address questions ranging from strategic to technical; and (iii) the creation and dissemination of community-developed teaching materials as well as the formulation of course, program, and curricular recommendations for education and workforce development that reflect the changing, data-centric approach in chemical research; (iv) providing access to a shared hardware infrastructure for community data sets, on-site data mining capacity, and the exploration of domain specific method and hardware issues.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.