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: 2324302
• 负责人: Brian Rose
• 金额: $ 48.95万
• 依托单位: SUNY at Albany
• 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=2324302&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.

该项目建立在两个社区驱动的开放地球科学努力的基础上：Pangeo 和 Project Pythia 拥有先进的云中“大数据”地球科学变革平台和范例；Pythia 为基于 Python 的开放、交互式学习资源。建立在对用户“有效”的公共云数据集上的地球科学工作流程 该项目的中心目标是通过使用 Pythia Cookbook 围绕共享科学工作流程知识建立社区，从而减少科学进步的障碍。 “Cookbooks”意味着用于转换原始成分（公开数据）的科学有用结果的食谱。Cookbooks 基于 Jupyter 笔记本，但明确与可重复的计算环境相关，并由丰富的基础设施支持，支持协作创作和自动健康检查。解决笔记本过时这一普遍问题的重要工具，开放获取、基于云的 Cookbook 是科学民主化的力量。贡献者和维护者，该项目将提高当前和未来的地球科学家在快速发展的开放科学生态系统中实践开放科学的能力。Pythia 项目的存在是为了容纳、共享和加速基于 Python 的高质量学习资源的开发该项目将通过使用 Pythia 团队将开发的开源生态系统在云中开发、记录和传播高度可扩展的可重复数据分析的最佳实践来推进地球科学研究和教育。科学驱动的示例食谱展示了针对多个地球科学领域的高价值数据集的通用分析工作流程的高度可扩展版本，其内容旨在提高社区意识和参与度。内容将跨越大气科学、物理海洋学、水文学、冰川学、气候科学等学科。以及机器学习的应用程序将在商业和 NSF 资助的云平台上部署高性能的数据接近的 Cookbook 创作、测试和使用。用户贡献者将通过年度研讨会、外展和课堂使用来扩大和发展，并专门针对服务不足的社区进行招募；优先事项将由独立指导委员会指导；通过培育一个由自动化支持的充满活力、包容性的社区来实现可持续性。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。