GitHub Repo: https://github.com/ESIPFed/Geoweaver
Pygeoweaver (Python Bindings): https://github.com/ESIPFed/pygeoweaver
Live Demo: https://geobrain.csiss.gmu.edu/Geoweaver
Geoweaver is an in-browser software allowing users to easily compose and execute full-stack data processing workflows via taking advantage of online spatial data facilities, high-performance computation platforms, and open-source deep learning libraries. It provides all-in-one capacity covering server management, code repository, workflow orchestration software, and history recorder.
It can be run from both local and remote (distributed) machines.
- Safely Store all your progress along the way.
- Stay organised and productive through out your years-long research
- Seamlessly connect to external servers with SSH.
- In-Built Web UI with full support for Python.
For further insights into Geoweaver, please explore the website at https://geoweaver.dev. GeoWeaver is a community effort. Any contribution is welcome and greatly appreciated!
- Host Management:
- Register machines via SSH as hosts for running processes.
- Add Jupyter Servers as host resources for interaction and workflow editing.
- Process Variety:
- Add various types of processes, such as bash scripts for data downloading.
- Jupyter Notebook Integration:
- Upload or import Jupyter notebooks.
- Intercept websocket traffic to save notebook versions, enabling easy revision history access.
- Process History and Logging:
- Detailed history of every process run, including logs and outputs, is stored.
- Workflow Management:
- Link processes to create workflows for parallel or sequential execution across different resources.
- All aspects of workflow management are centralized within GeoWeaver.
- Boosts Data Pipeline's Tangibility:
- Geoweaver provides an intuitive, interactive interface for visualizing data workflows, making it easier for users to understand and manage complex data pipelines.
- This clear visualization helps users to see the connections and dependencies between different components of their workflows.
- Enhances Research Productivity and Reduces Work Anxiety:
- Geoweaver has automated scheduling and execution of tasks, researchers can set up their workflows to run at specified times or conditions without manual intervention.
- This automation reduces the burden of monitoring and manual execution, allowing researchers to focus on analysis and innovation.
Geoweaver is a powerful tool for geospatial data processing, offering a range of features and capabilities. This guide will walk you through the steps to install Geoweaver on your system.
Before you begin, ensure that you have the following dependencies installed:
- Java 1.8 or higher (OpenJDK 8 or higher)
- Docker (required only for the Docker installation method)
A live demo site is available.
Learn more about Geoweaver in its official documentation at https://esipfed.github.io/Geoweaver/docs/install.html
PyGeoWeaver is a Python package that provides a convenient and user-friendly interface to interact with GeoWeaver, a powerful geospatial data processing application written in Java. With PyGeoWeaver, Jupyter notebook and JupyterLab users can seamlessly integrate and utilize the capabilities of GeoWeaver within their Python workflows.
Please do visit the PyGeoWeaver GitHub repository.
Thanks to our many contributors!
The first stable release of Geoweaver was launched in July 2020 after nearly a year of active development. Key features included:
- Support for various vector and raster data formats
- Interactive mapping with pan, zoom, and layer control
- Basic geoprocessing tools (buffer, clip, dissolve, etc.)
- Python scripting interface for automation
Despite being an early version, Geoweaver quickly gained traction among GIS enthusiasts and developers due to its modern architecture and extensibility.
After incorporating feedback from the user community, the Geoweaver team released version 2.0 in March 2022. This major update focused on performance improvements and added several highly requested features:
- Multiprocessing support for faster geoprocessing
- 3D visualization and terrain analysis tools
- Improved symbology and labeling options
- Integration with popular spatial databases
Version 2.0 solidified Geoweaver's position as a powerful open-source GIS solution and attracted interest from various industries and research institutions.
The Geoweaver development team is currently working on version 3.0, which is expected to be released in late 2024.
With each new release, the Geoweaver project continues to push the boundaries of open-source GIS software, providing users with a flexible and powerful platform for spatial data management and analysis.
If you found Geoweaver helpful in your research, please cite:
Sun, Z. et al., "Geoweaver: Advanced cyberinfrastructure for managing hybrid geoscientific AI workflows." ISPRS International Journal of Geo-Information 9, no. 2 (2020): 119.
Sun, Ziheng, Nicoleta C. Cristea, Kehan Yang, Ahmed Alnuaim, Lakshmi Chetana Gomaram Bikshapathireddy, Aji John, Justin Pflug et al. "Making machine learning-based snow water equivalent forecasting research productive and reusable by Geoweaver." In AGU fall meeting abstracts, vol. 2022, pp. IN23A-04. 2022.
Sun, Ziheng, and Nicoleta Cristea. "Geoweaver for Automating ML-based High Resolution Snow Mapping Workflow." In AGU Fall Meeting Abstracts, vol. 2021, pp. IN11C-07. 2021.
Sun, Ziheng, Liping Di, Jason Tullis, Annie Bryant Burgess, and Andrew Magill. "Geoweaver: Connecting Dots for Artificial Intelligence in Geoscience." In AGU Fall Meeting Abstracts, vol. 2020, pp. IN011-02. 2020.
Sun, Ziheng, Liping Di, Annie Burgess, Jason A. Tullis, and Andrew B. Magill. "Geoweaver: Advanced cyberinfrastructure for managing hybrid geoscientific AI workflows." ISPRS International Journal of Geo-Information 9, no. 2 (2020): 119.
Sun, Ziheng, Liping Di, Jason Tullis, Annie Bryant Burgess, and Andrew Magill. "Geoweaver: Connecting Dots for Artificial Intelligence in Geoscience." In AGU Fall Meeting Abstracts, vol. 2020, pp. IN011-02. 2020.
The MIT License (MIT)
Copyright (c) 2015 Chris Kibble
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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