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.

北极是地球剩余的边界之一，这对于地球的气候系统至关重要。气候变化和多年冻土变暖在整个北极都记录在整个北极中，这种变暖释放了温室气体，进一步推动了全球变暖。北极生态系统已被推到临界点，对内陆和沿海景观产生了巨大影响：土壤碳通量改变，植被覆盖率的变化，侵蚀，动物行为的转变以及对基础设施的挑战。随着这种通过降解多年冻土和融化的海水转化为水的转变，并通过整个北极生态系统回荡，对北极变化的理解需要从广泛的地球，工程和社会科学学科中进行研究。存在有价值的气候，地质，生物学和社会学数据，但北极科学界尚未完全利用。人工智能（AI）和机器学习方法具有自动处理大数据并提取隐藏知识的能力，这将使研究人员能够充分利用这些数据来应对各种北极挑战。该项目将开发一项新型的网络训练计划，以提高各学科跨学科的无数北极研究人员在北极数据上采用AI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的数据驱动的发现工具，从而更好地理解迅速变化的北极格局，这对于社会福利至关重要。人工智能已成为最强大的工具，成为分析大数据的最强大工具之一，并启用了新的数据驱动科学的新范围。但是，在当前的本科和研究生课程以及活跃的北极研究人员中，在这些新兴主题中进行的培训在很大程度上缺少。该项目将通过一系列补充和相互加强的培训活动来发展数据科学技能，从而促进北极科学劳动力的发展。将建立一个北极研究网络，以收集AI培训需求，并供北极科学家和AI专家共享思想和资源，相互联系，并通过每月的网络研讨会系列体验最新的研究进展。定制的培训将通过面对面的研讨会和在线，自定进度的学习计划提供，以扩大对北极科学中先进的AI方法的采用。这些讲习班将不仅向北极研究人员开放，还向北极科学教育工作者开放，为多个机构的感兴趣的教职员工和讲师提供途径，以将培训材料纳入其课程和课堂教学，从而扩大了网络培养活动的规模。同时，一项公开竞争，即北极Geoai挑战赛，将作为动手技术培训的一种新型形式推出，以吸引才华横溢的人开发新颖的AI解决方案，以解决现实世界中的北极大数据问题。招聘计划将培养一种包容性和多样化的社区文化，重点关注STEM研究劳动力，有更多的妇女，有色人种以及来自不同种族的妇女，各种族裔，学术背景和部门的人，特别是使北极土著社区在理解和缓解北极变化方面具有更大的声音。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，以确保在所有北极科学和地球科学领域及其他所有北极科学和地球上的网络基础设施使用者，专业人员和开发人员的长期访问。该项目由地球科学局与高级网络基础设施办公室之间的合作共同资助，以支持AI/ML和地球科学中的开放科学活动。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和广泛影响的评估来通过评估来支持的。