Collaborative Research: CyberTraining: Implementation: Medium: Cyber Training for Open Science in Climate, Water and Environmental Sustainability

气候、水和环境（CWE）的可持续性对于维持美国和世界的整体福祉至关重要。应对当前CWE可持续发展的挑战需要大数据分析、模拟、高性能计算和先进网络基础设施的知识和技能。然而，他们缺乏整合和处理来自不同来源的数据的培训机会，以供学生进行CWE研究。其中包括数据质量控制、分析、可视化和模拟。该项目通过创建CWE可持续性网络培训课程填补了这一空白，该课程建立在以往成功的基础上，并结合了可查找、可访问、可互操作和可重复使用（FAIR）科学领域快速发展的技术和社区最佳实践。该项目利用公开的数据、仿真工具和计算资源，为学生、培训师和在职专业人员提供网络培训。该项目开发了一个CWE网络培训课程，提供三个层次的培训：(i)基础水平，可用于多个学科和受众；（ii）教授CWE领域特定领域数据和网络工具知识的专家级别；以及（iii）提供高级网络基础设施培训以解决CWE可持续性问题的开发人员级别。该课程建立在一个经过验证的灵活的模块化方法上，可以以一系列学分课程、非学分证书和学位证书课程的形式实施。这个CWE网络培训课程将透过开放及可扩展的网上平台传播，以克服技术障碍，使更广泛的采用和社区贡献。这个独特的平台不仅可以传播课程，还可以为共同开发和实施课程提供工具和资源。该项目由一个多学科团队共同领导，该团队在开发面对面和在线学习模块、网络数据、计算工具和平台方面具有丰富的经验，并根据社区需求将这些工具纳入其本科和研究生课程。该项目将通过与少数族裔服务机构的合作，直接培训五所大学、三所社区学院和一所高中的学生。该项目由地球科学理事会和先进网络基础设施办公室共同资助，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。

Climate, Water and Environment (CWE) sustainability is critical for maintaining the overall well-being of the United States and the world. Addressing the current challenges in CWE sustainability requires knowledge and skills of big data analytics, simulations, high-performance computing, and advanced cyberinfrastructures. Yet, their are inadequate training opportunities on integrating and working with data from different sources available to student for CWE research. These include data quality control, analysis, visualization, and simulations. This project fills this gap by creating a CyberTraining curriculum for CWE sustainability that builds on previous successes and incorporates rapidly-developing technology and community best practices in Findable Accessible Interoperable and Reusable (FAIR) Science. This project provides CyberTraining to students, trainers and working professionals using publicly available data, simulation tools, and computing resources. This project develops a CWE CyberTraining curriculum to provide training at three levels: (i) foundation level that can be used across multiple disciplines and audiences; (ii) expert level that teaches domain specific data and cyber tools knowledge in CWE domains; and (iii) developer level that provides advanced cyberinfrastructure training for addressing CWE sustainability problems. This curriculum builds upon a proven flexible modular approach, and can be implemented in the form of a sequence of credit courses, non-credit certificates, and degree certificate programs. This CWE CyberTraining curriculum will be disseminated through an open and scalable online platform to overcome technology barriers and enable broader adoption and community contribution. This unique platform will not only disseminate the curriculum, but also provide access to the tools and resources to co-develop and implement the curriculum. The project is co-led by a multi-disciplinary team that has rich experience in developing in-person and online learning modules, cyber-enabled data, computation tools, and platforms driven by community needs, and additionally incorporating these tools in their undergraduate and graduate courses. This project will directly train students at five universities, three community colleges and one high school through its partnership with minority serving institutions. 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.