Findable Accessible Interoperable and Reusable (FAIR) Hackathon Workshop for Mathematical and Physical Sciences (MPS) Research Communities

FAIR原则（可查找、可访问、可互操作和可重用）在应用于科学研究数据时，有可能减轻NSF资助的研究为共享而创建的数据的准备负担，并增强数据的使用和重用。FAIR数学和物理科学（MPS）研究社区黑客马拉松研讨会将汇集由NSF资助的物理科学项目的创新数据科学家和开发人员，使用FAIR原则解决现实世界的数据挑战：可查找、可访问、可互操作和可重用数据。旨在解决公众访问数据的问题，并为研究人员提供工具和相关的实践经验，研讨会将利用由欧洲开放科学云的欧盟GOFAIR倡议组织的bioit World FAIR数据黑客马拉松的成功模式，在黑客马拉松的背景下制定FAIR原则和指标。黑客马拉松将联合MPS和研究数据管理团队，以最大的影响潜力处理实际数据集。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The FAIR principles (findable, accessible, interoperable, and reusable) when applied to scientific research data have the potential to both ease the burden of readying data created from NSF funded research for sharing and enhance the use and reuse of the data. The FAIR Hackathon Workshop for Mathematics and the Physical Sciences (MPS) research communities will bring together innovative data scientists and developers from across physical sciences projects funded by NSF to solve real-world data challenges using the principles of FAIR: Findable, Accessible, Interoperable and Reusable Data. Designed to address issues of public access to data and to provide tools and relevant hands-on experience for researchers, the workshop will lay out the FAIR principles and metrics in the context of a hackathon using the successful model of The Bio-IT World FAIR Data Hackathon organized by the European Union's GOFAIR initiative of the European Open Science Cloud. The hackathon will unite MPS and research data management teams to tackle actual datasets with maximum impact potential.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.