CyberTraining: CIU:Cross-disciplinary Training for Findable, Accessible, Interoperable, and Reusable (FAIR) science

应对与人口增长、粮食和水安全、频繁发生的自然灾害和气候变化相关的重大挑战，不仅需要地球科学领域的专业知识，还需要处理大数据分析和模拟的计算（网络）技能。然而，在为学生提供网上培训方面存在许多挑战，包括教师的学习曲线陡峭，时间承诺和缺乏培训材料方面的资源。该项目为地球科学专业的学生和工作人员创建网络培训计划，其形式为模块或实验室，用于现有课程，独立的单学分课程，夏季研讨会和靴子营地。学生接受培训，运行国家的最先进的数值模型，并在分析大量的模拟和观测数据集与先进的数据分析工具。总体目标是培养新一代科学家来管理数据丰富和计算密集型的任务，从而在STEM领域具有全球竞争力，从而实现NSF促进科学进步的使命。 该项目的培训部分将使科学公开可用，并使用可查找，可扩展，可互操作和可重用（FAIR）科学的最佳实践透明地再现。该项目的受训人数估计约为200名普渡大学的学生和400多名普渡大学以外的学生、教师和工作专业人员。该项目通过在普渡大学等多个机构举办课程、研讨会和靴子营，培训学生和工作专业人员，将网络支持的最先进的计算工具付诸实践。新罕布什尔州大学和亚拉巴马大学。该项目创建了一个网络培训课程，其驱动因素是需要获得以下六个领域的专门知识：数据访问、地理处理、时间序列分析、计算模拟、可视化和出版。这些领域构成了模块化网络培训框架的基础，该框架支持针对地球科学学习者的培训材料的开发和实施。创新在于通过为学生和工作专业人员提供一系列灵活的培训选择来加强地球科学课程，包括网络培训。公平网络培训（FACT）奖学金将提高研究生的计算思维，并创造一个途径，利用最有才华的学生来培养下一代精通网络的地球科学家。该奖项体现了NSF的法定使命，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。

Addressing the grand challenges associated with growing population, food and water security, frequently occurring natural disasters, and changing climate requires not only geoscience domain expertise, but also computational (cyber) skills to deal with big data analytics and simulations. However, many challenges exist in providing cyber training to students, including steep learning curve for instructors, time commitment and lack of resources in terms of training material. This project creates cyber training programs for earth science students and working professional in the form of modules or labs for use in an existing course, an independent one-credit course, summer workshops and boot camps. Students receive training in running state-of-the-art numerical models, and in analyzing massive simulated and observational data sets with advanced data analysis tools. The overall goal is to create a new generation of scientists to manage data-rich and computationally intensive tasks to become globally competitive in the STEM, thus fulfilling NSF's mission to promote the progress of science. The training component of the project will make the science openly available and transparently reproducible using the best practices in Findable, Accessible, Interoperable, and Reusable (FAIR) science. The estimated number of trainees from this project is approximately 200 students at Purdue and potentially more than 400 students, faculty and working professionals outside Purdue.This project brings cyber-enabled state-of-the-art computational tools into practice by training students and working professionals through courses, workshops and boot camps at multiple institutions, including Purdue University, University of New Hampshire and University of Alabama. The project creates a cyber training curriculum that is driven by the need to acquire expertise in the following six areas: data access, geo-processing, time series analysis, computational simulation, visualization and publication. These areas form the foundation of a modular cyber training framework that supports development and implementation of training materials targeting geoscience learners. The innovation lies in enhancing geosciences curriculum to include cyber training by providing a range of flexible training options for students and working professionals. A FAIR Cyber Training (FACT) Fellowship will enhance computational thinking among graduate students and create an avenue to tap the most talented students to train the next generation of cyber savvy earth scientists. This interdisciplinary collaboration from hydrology, climate science, computer science and instruction design expertise enables holistic training covering both domain science and computational technology.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.