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

• Published in: Earth and space science (Hoboken, N.J.) Vol. 12; no. 5
• Main Authors: Nodjoumi, G., Brandt, C. H., Suárez‐Valencia, J. E., Luzzi, E., Valiante, M., Rossi, A. P.
• Format: Journal Article
• Language: English
• Published: Hoboken John Wiley & Sons, Inc 01.05.2025
• Subjects: Access control; Algorithms; Collaboration; Containers; Data processing; Data science; FAIR; Flexibility; Geologic mapping; Geology; Infrastructure; Integrated software; interoperability; JupyterHub; Mapping; Mars; NASA ASP; Open source software; Python; Resource management; Scientists; Solar system; Spectrometers; USGS ISIS; Work environment
• ISSN: 2333-5084; 2333-5084
• DOI: 10.1029/2025EA004251

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. Plain Language Summary A shared web interface on JupyterHub simplifies collaborative coding for multiple users. To avoid individual software installations, JupyterHub leverages Docker containers to package necessary programs and libraries, enabling scientists to use a consistent setup through a web browser. The Europlanet Geologic MApping of Planetary surfaces (GMAP) project uses this setup to streamline the processing of space mission data from Mars, the Moon, and other celestial bodies. Researchers can directly utilize key tools like Integrated Software for Imagers and Spectrometers and the NASA Ames Stereo Pipeline within Jupyter notebooks for image processing and 3D map/model creation. Because all essential parts are bundled in Docker images, these tools function seamlessly. This approach avoids installation problems, saves time, and standardizes the work environment for all users of these containers. The integration of these tools in a shared online space makes data, script, and result sharing easier for teams. Consistent research is encouraged, and data processing is simplified for even novice users. With its container‐based design, GMAP's JupyterHub setup allows scientists to prioritize planetary scientific discoveries over software configuration complexities. Key Points JupyterHub facilitates multi‐user access to computational resources and promotes reproducibility in data analysis A Docker‐based USGS Integrated Software for Imagers and Spectrometers and the NASA Ames Stereo Pipeline, allows efficient geospatial and stereogrammetric processing of planetary data The Europlanet GMAP initiative promotes FAIR practices in planetary science via open‐source platforms and training programs