Collaborative Research: GEO OSE Track 2: Project Pythia and Pangeo: Building an inclusive geoscience community through accessible, reusable, and reproducible workflows

合作研究：GEO OSE 第 2 轨道：Pythia 和 Pangeo 项目：通过可访问、可重用和可重复的工作流程构建包容性的地球科学社区

• 批准号: 2324303
• 负责人: John Clyne
• 金额: $ 71.04万
• 依托单位: University Corporation For Atmospheric Res
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2324303&HistoricalAwards=false
• 关键词: Collaborative; Research; GEO; OSE; Track

This project builds upon the demonstrable success of two community-driven open geoscience efforts: Pangeo and Project Pythia. Pangeo has advanced transformative platforms and paradigms for “Big Data” geoscience in the cloud; Pythia has built open, interactive learning resources for Python-based geoscience workflows built on public cloud datasets that “just work” for users. The central goal of this project is to reduce barriers to scientific progress by building community around shared scientific workflow knowledge, using the Pythia Cookbook format. “Cookbooks” imply collections of recipes for transforming raw ingredients (publicly available data) into scientifically useful results. Cookbooks are based on Jupyter notebooks but explicitly tied to reproducible computational environments and supported by a rich infrastructure enabling collaborative authoring and automated health-checking – essential tools in the struggle against the widespread problem of notebook obsolescence. Open-access, cloud-based Cookbooks are a democratizing force for science. By growing the collection of Pythia Cookbooks while growing the community of users, contributors, and maintainers, this project will grow the capacity of current and future geoscientists to practice open science within the rapidly evolving open science ecosystem.Project Pythia exists to house, share, and accelerate the development of high-quality learning resources for Python-based computing in the geosciences. This project will advance geoscience research and education by developing, documenting, and propagating best practices for highly scalable reproducible data analysis in the cloud using the open-source ecosystem. The Pythia team will develop science-driven exemplar Cookbooks demonstrating highly scalable versions of common analysis workflows on high-value datasets across numerous geoscience domains, with content chosen to accelerate community awareness and participation. Content will span disciplines including Atmospheric Science, Physical Oceanography, Hydrology, Glaciology, Climate Science, and applications of Machine Learning. Infrastructure will be deployed for performant data-proximate Cookbook authoring, testing, and use, on both commercial and NSF-funded cloud platforms. Both the Cookbook collection and the community of user-contributors will broaden and grow through annual workshops, outreach, and classroom use, with recruitment specifically targeting under-served communities. Priorities will be guided by an independent steering board; sustainability will be achieved by nurturing a vibrant, inclusive community backed by automation that lowers barriers to participation.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.

该项目基于两个社区驱动的开放地球科学努力的明显成功：Pangeo和Project Pythia。 Pangeo具有云中“大数据”地球科学的高级变革平台和范例； Pythia为基于Python的地球科学工作流程建立了开放的交互式学习资源，该工作流构建在公共云数据集上，这些数据集“仅适用于用户”。该项目的核心目标是通过使用毕达利亚食谱格式围绕共享的科学工作流知识建立社区来减少科学进步的障碍。 “食谱”意味着将原始in Redredients（公开数据）转换为科学有用的结果的食谱集合。食谱是基于jupyter笔记本，但明确地与重现计算环境相关，并由丰富的基础架构提供支持，从而实现了协作创作和自动化健康检查 - 与抗议笔记本的宽广问题的基本工具。基于云的开放式食谱是科学的民主化力量。通过在种植用户，贡献者和维护者社区的同时，通过种植Pythia食谱的收集，该项目将提高现行和未来的地球科学家在迅速发展的开放科学生态系统中实践开放科学的能力。ProthiaPythia的存在，共享，共享和加速基于Python基于Python的计算机的高级学习资源。该项目将通过使用开源生态系统在云中开发，记录和传播最佳的可重复数据分析，通过开发，记录和传播最佳实践来推动地球科学研究和教育。 Pythia团队将开发以科学为导向的典范食谱，这些食谱在众多地球科学领域的高价值数据集上展示了高度可扩展的分析工作流程，并选择了内容来加速社区的意识和参与。内容将涵盖学科，包括大气科学，物理海洋学，水文学，冰川学，气候科学以及机器学习的应用。将在商业和NSF资助的云平台上部署基础架构，以供表现数据 - 耐数据的烹饪书创作，测试和使用。食谱集和用户企业社区都将通过年度研讨会，外展和课堂使用来扩大和发展，并招募专门针对服务不足的社区。优先事项将由独立指导委员会指导；可持续性将通过培育一个充满活力的包容性社区，并以自动化为支持，从而降低了参与障碍。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子和更广泛的影响评估审查标准来评估，被认为是宝贵的支持。