Cybertraining: Pilot: Collaborative Research: Cybertraining for Earth Surface Processes Modelers

网络培训：试点：协作研究：地球表面过程建模者的网络培训

• 批准号: 1924185
• 负责人: Nicole Gasparini
• 金额: $ 2.15万
• 依托单位: Tulane University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1924185&HistoricalAwards=false
• 关键词: Cybertraining; Pilot; Collaborative; Research; Earth

Living sustainably on a rapidly changing planet is one of the greatest modern scientific and societal challenges. One critical aspect of global change involves the earth's surface itself: the rearrangement of its landforms, soils, and sediments by processes such as landslides, debris flows, floods, and coastal erosion. The Community Surface Dynamics Modeling System, CSDMS, creates cyberinfrastructure to enable advanced numerical models of the earth's surface, its changes through time, and the influence of human activity. However, traditional earth science education does not usually equip students with skills to become effective cyberinfrastructure users and cyberinfrastructure contributors. In order to develop innovative models for analyzing and predicting how the earth's surface responds to environmental change and human influence, the earth surface processes (ESP) modeling community needs a platform to teach modern programming practices and High Performance Computing methods. This project implements a 10-day Cyberinfrastructure in Earth Surface Processes Institute (ESPIn) for graduate students, postdoctoral fellows and early career faculty at the CSDMS Integration Facility at the University of Colorado in Boulder in the summers of 2020-2021 trains the next generation to be innovators. ESPIn aims to transcend the traditional model of department-based graduate education through interdisciplinary, problem-based, "Just in Time Teaching" of model use and development. Over forty participants, selected from diverse disciplinary backgrounds with explicit slots reserved for underrepresented minorities, gain direct experience in converting their research codes into open-source distributed software. ESPIn hosts developed lesson material in online open access educational repositories. ESPIn helps to train a new generation of computationally savvy, integrative scientists, while accomplishing major community science priorities. This project thus serves the national interest, as stated by NSF's mission: to promote the progress of science; to advance the national prosperity and welfare by building a capable geoscience workforce.The Earth Surface Processes Institute (ESPIn) is a 10-day immersive experience for graduate students, postdoctoral fellows and early career faculty, allowing them to make advances on critical earth surface processes research questions with state-of-the-art modeling tools. This project targets learners who would benefit from critical knowledge, skills, and tools to become better cyberinfrastructure users and developers through a careful, inclusive selection procedure. This project aims to help make scientific advances in the study of Earth Surface Processes (ESP) that leverage the powerful and advanced capabilities of new cybertools, such as the Python Modeling Tool. To these ends, the primary objective is to expand the use of cyberinfrastructure among members of the ESP research community with training that (1) increases their competence and confidence with using cyberinfrastructure tools, methods, and resources and (2) moves the larger ESP community towards more widely adopting tools to advance the fundamental science of predicting surface change. Experienced scientists, visiting faculty, and software engineers assist with training and mentoring of the participants. ESPIn offers hands-on training in best programming practices, numerical methods, open source software development, advanced use of version control systems, writing unit tests, HPC-based sensitivity testing and model uncertainty quantification techniques. Several days are dedicated to working collaboratively on research and coding projects. Participants work on developing their own codes, with the intent of making codes more robust and compliant with existing ESP CI frameworks. The Summer Institute is quantitatively evaluated for learning efficacy and evaluations are used to iterate on lesson material quality. ESPIn provides all developed lesson material as online learning and teaching modules and broadly advertises these resources to the geoscience community.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.

在快速变化的星球上可持续地生活是现代科学和社会面临的最大挑战之一。全球变化的一个关键方面涉及地球表面本身：通过山体滑坡、泥石流、洪水和海岸侵蚀等过程重新排列地貌、土壤和沉积物。社区表面动力学建模系统 (CSDMS) 创建网络基础设施，以实现地球表面、其随时间的变化以及人类活动影响的高级数值模型。然而，传统的地球科学教育通常并不能让学生具备成为有效的网络基础设施用户和网络基础设施贡献者的技能。为了开发创新模型来分析和预测地球表面如何响应环境变化和人类影响，地球表面过程 (ESP) 建模社区需要一个平台来教授现代编程实践和高性能计算方法。该项目于 2020 年至 2021 年夏季在地球表面过程研究所 (ESPIn) 为研究生、博士后研究员和早期职业教师在博尔德科罗拉多大学 CSDMS 集成设施实施为期 10 天的网络基础设施，培训下一代创新者。 ESPIn旨在通过跨学科的、基于问题的、“及时教学”的模型使用和开发，超越院系研究生教育的传统模式。四十多名参与者从不同的学科背景中选出，并为代表性不足的少数群体保留了明确的席位，他们在将他们的研究代码转换为开源分布式软件方面获得了直接经验。 ESPIn 在在线开放获取教育存储库中托管开发的课程材料。 ESPIn 帮助培养新一代精通计算、综合的科学家，同时完成主要的社区科学优先事项。因此，该项目符合国家利益，正如 NSF 的使命所言：促进科学进步；通过建设一支有能力的地球科学劳动力来促进国家繁荣和福祉。地球表面过程研究所 (ESPIn) 为研究生、博士后研究员和早期职业教师提供为期 10 天的沉浸式体验，使他们能够利用最先进的建模工具在关键的地球表面过程研究问题上取得进展。该项目针对那些将从关键知识、技能和工具中受益的学习者，通过仔细、包容的选择程序成为更好的网络基础设施用户和开发人员。该项目旨在利用 Python 建模工具等新型网络工具的强大和先进功能，帮助地球表面过程 (ESP) 研究取得科学进展。为此，主要目标是通过培训扩大 ESP 研究社区成员对网络基础设施的使用，(1) 提高他们使用网络基础设施工具、方法和资源的能力和信心；(2) 推动更大的 ESP 社区更广泛地采用工具，以推进预测地表变化的基础科学。 经验丰富的科学家、客座教师和软件工程师协助培训和指导参与者。 ESPIn 提供有关最佳编程实践、数值方法、开源软件开发、版本控制系统的高级使用、编写单元测试、基于 HPC 的敏感性测试和模型不确定性量化技术的实践培训。几天的时间致力于在研究和编码项目上进行协作。参与者致力于开发自己的代码，目的是使代码更加健壮并符合现有 ESP CI 框架。暑期学院的学习效果进行定量评估，评估用于迭代课程材料的质量。 ESPIn 将所有开发的课程材料作为在线学习和教学模块提供，并向地球科学界广泛宣传这些资源。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。