Collaborative Research: CyberTraining: Implementation: Medium: Cyber2A: CyberTraining on AI-driven Analytics for Next Generation Arctic Scientists

合作研究：网络培训：实施：媒介：Cyber​​2A：下一代北极科学家人工智能驱动分析的网络培训

• 批准号: 2230035
• 负责人: Anna Liljedahl
• 金额: $ 31.94万
• 依托单位: Woodwell Climate Research Center, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2230035&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Implementation; Medium

The Arctic is one of the Earth's remaining frontiers that is critical to the Earth's climate systems. Climate change and permafrost warming are documented across the Arctic, with such warming releasing greenhouse gasses that further drive global warming. The Arctic ecosystem has been pushed to a tipping point with dramatic impacts to inland and coastal landscapes: altered soil carbon fluxes, changes in vegetation cover, erosion, shifts in animal behavior, and challenges to infrastructure. As this transformation of ice to water through degrading permafrost and melting sea and lake ice reverberates through the entire Arctic ecosystem, understanding of Arctic change necessitates research from a broad range of Earth, engineering, and social science disciplines. Valuable climatic, geological, biological, and sociological data exist but have yet to be fully exploited by the Arctic science community. Artificial Intelligence (AI) and machine learning approaches, which have the ability to automatically process big data and extract hidden knowledge, would enable researchers to make the best possible use of these data to address diverse Arctic challenges. This project will develop a novel cybertraining program to increase the capacity for myriad Arctic researchers across disciplines to employ AI-driven techniques on Arctic data. These new skills will enable current and future Arctic scientists to use the new wave of data-driven discovery tools and thereby better understand the rapidly changing Arctic landscape, which is critically needed for societal welfare.Today, Artificial Intelligence has become one of the most powerful tools to analyze big data and enable a new paradigm of data-driven science. However, training in these emerging topics is largely missing in current undergraduate and graduate curricula, as well as for active Arctic researchers. This project will foster the growth of an Arctic science workforce by developing data science skills through a series of complementary and mutually reinforcing training activities. An Arctic-AI research network will be established for collecting AI training needs and for Arctic scientists and AI experts to share ideas and resources, to network with each other, and to experience the latest research advances through a monthly webinar series. Customized training will be provided through both in-person workshops and online, self-paced learning programs to broaden the adoption of advanced AI methods in Arctic science. The workshops will be open not only to Arctic researchers, but also to the Arctic science educators, offering a pathway for interested faculty and instructors at multiple institutions to incorporate training materials into their curricula and classroom teaching, amplifying the scale of the cybertraining activities. Meanwhile, an open competition, the Arctic GeoAI Challenge, will be launched as a novel form of hands-on technology training to attract talented individuals to develop novel AI solutions for solving a real-world Arctic big data problem. The recruitment plan will cultivate an inclusive and diverse culture of community, with a strong focus on growing the STEM research workforce with more women, women of color, and people from diverse ethnic groups, academic backgrounds, and sectors, enabling especially the Arctic indigenous community to have a greater voice in understanding and mitigating Arctic change. All training materials will be deposited in the Arctic Data Center's Learning Hub and the Permafrost Discovery Gateway to ensure long-term access by cyberinfrastructure users, professionals, and developers across all Arctic science and geoscience domains and beyond. This project is co-funded by a collaboration between the Directorate for Geosciences and Office of Advanced Cyberinfrastructure to support AI/ML and open science activities in the geosciences.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.

北极是地球仅存的边界之一，对地球气候系统至关重要。整个北极地区都有气候变化和永久冻土变暖的记录，这种变暖会释放温室气体，进一步推动全球变暖。北极生态系统已被推向临界点，对内陆和沿海景观产生巨大影响：土壤碳通量改变、植被覆盖变化、侵蚀、动物行为变化以及基础设施面临的挑战。由于永久冻土退化以及海冰和湖冰融化所导致的冰向水的转变会影响整个北极生态系统，因此了解北极变化需要广泛的地球、工程和社会科学学科的研究。有价值的气候、地质、生物和社会学数据已经存在，但尚未被北极科学界充分利用。人工智能（AI）和机器学习方法能够自动处理大数据并提取隐藏知识，使研究人员能够最好地利用这些数据来应对各种北极挑战。该项目将开发一个新颖的网络培训计划，以提高跨学科的无数北极研究人员在北极数据上应用人工智能驱动技术的能力。这些新技能将使当前和未来的北极科学家能够使用新一波数据驱动的发现工具，从而更好地了解快速变化的北极景观，这对于社会福利至关重要。如今，人工智能已成为分析大数据和实现数据驱动科学新范式的最强大工具之一。然而，当前的本科生和研究生课程以及活跃的北极研究人员很大程度上缺乏对这些新兴主题的培训。该项目将通过一系列互补和相辅相成的培训活动来培养数据科学技能，从而促进北极科学劳动力的发展。将建立北极人工智能研究网络，收集人工智能培训需求，并让北极科学家和人工智能专家分享想法和资源，相互联系，并通过每月一次的网络研讨会系列体验最新的研究进展。将通过现场研讨会和在线自定进度学习计划提供定制培训，以扩大先进人工智能方法在北极科学中的采用。这些研讨会不仅向北极研究人员开放，还向北极科学教育者开放，为多个机构感兴趣的教师和讲师提供了一个途径，将培训材料纳入他们的课程和课堂教学，扩大网络培训活动的规模。与此同时，将推出一项名为“北极地理人工智能挑战赛”的公开竞赛，作为一种新颖的实践技术培训形式，以吸引人才开发新颖的人工智能解决方案，以解决现实世界的北极大数据问题。招聘计划将培养包容性和多元化的社区文化，重点是培养更多女性、有色人种女性以及来自不同种族、学术背景和部门的 STEM 研究人员，特别是使北极土著社区在理解和减缓北极变化方面拥有更大的发言权。所有培训材料都将存放在北极数据中心的学习中心和永久冻土发现网关中，以确保所有北极科学和地球科学领域及其他领域的网络基础设施用户、专业人员和开发人员能够长期访问。该项目由地球科学理事会和高级网络基础设施办公室合作共同资助，以支持地球科学领域的人工智能/机器学习和开放科学活动。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。