Collaborative and Reproducible Planetary Science Through the Europlanet GMAP JupyterHub Processing Environment

IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS
G. Nodjoumi, C. H. Brandt, J. E. Suárez-Valencia, E. Luzzi, M. Valiante, A. P. Rossi
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引用次数: 0

Abstract

JupyterHub is an open-source system enabling multiple users to access individual computational environments. This facilitates collaborative development and execution of Jupyter notebooks, Python scripts, and other tools among researchers and educators through a unified interface. Through the integration of container technologies, including Docker, JupyterHub achieves seamless scalability for numerous users while maintaining efficient computational resource management. This flexible approach is especially useful in specialized areas like planetary data science, which requires robust and reproducible workflows to manage large volumes of mission data. The Europlanet Geologic MApping of Planetary surfaces (GMAP) project employs a Docker-based JupyterHub deployment to centralize essential data processing tools, such as the Integrated Software for Imagers and Spectrometers (ISIS) and the NASA Ames Stereo Pipeline (ASP). These open-source tools facilitate tasks ranging from image calibration and map projection to stereogrammetry and 3D modeling. The deployment of these elements within Docker containers facilitates simplified installation and consistent performance across disparate hardware configurations. The use of pre-configured image formats within ISIS, ASP, and other GIS and Python libraries allows planetary scientists to efficiently process raw data into analytical products, including Digital Terrain Models. Additionally, JupyterHub's architecture enables secure collaboration via authentication methods (e.g., OAuth, GitHub), with concurrent provision for private and shared data directories. This integrated framework promotes reproducible research by streamlining the sharing of scripts, notebooks, and workflows. The GMAP JupyterHub platform significantly accelerates scientific discovery through the reduction of technical barriers, the promotion of standardization, and the provision of global access to planetary data science resources.

通过Europlanet GMAP JupyterHub处理环境的协作和可复制行星科学
JupyterHub是一个开源系统,允许多个用户访问单独的计算环境。这有助于通过统一的界面在研究人员和教育工作者之间协作开发和执行Jupyter笔记本、Python脚本和其他工具。通过集成包括Docker在内的容器技术,JupyterHub在保持高效计算资源管理的同时,为众多用户实现了无缝的可扩展性。这种灵活的方法在行星数据科学等专业领域特别有用,因为这些领域需要强大且可重复的工作流程来管理大量任务数据。Europlanet行星表面地质测绘(GMAP)项目采用基于docker的JupyterHub部署来集中基本数据处理工具,如成像仪和光谱仪集成软件(ISIS)和NASA Ames立体管道(ASP)。这些开源工具促进了从图像校准和地图投影到立体测量和3D建模的任务。在Docker容器中部署这些元素有助于简化安装,并在不同的硬件配置中保持一致的性能。在ISIS、ASP和其他GIS和Python库中使用预配置的图像格式,使行星科学家能够有效地将原始数据处理成分析产品,包括数字地形模型。此外,JupyterHub的架构通过认证方法(例如,OAuth, GitHub)实现安全协作,并并发提供私有和共享数据目录。这个集成的框架通过简化脚本、笔记本和工作流的共享来促进可重复的研究。GMAP JupyterHub平台通过减少技术障碍、促进标准化和提供对行星数据科学资源的全球访问,显著加速了科学发现。
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来源期刊
Earth and Space Science
Earth and Space Science Earth and Planetary Sciences-General Earth and Planetary Sciences
CiteScore
5.50
自引率
3.20%
发文量
285
审稿时长
19 weeks
期刊介绍: Marking AGU’s second new open access journal in the last 12 months, Earth and Space Science is the only journal that reflects the expansive range of science represented by AGU’s 62,000 members, including all of the Earth, planetary, and space sciences, and related fields in environmental science, geoengineering, space engineering, and biogeochemistry.
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