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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.

Why choose Geoweaver? 1) Safely Store all your progress along the way. 2) Stay organised and productive through out your years-long research 4) Seamlessly connect to external servers with SSH. 5) In-Built Web UI with full support for Python.

GeoWeaver is a community effort. Any contribution is welcome and greatly appreciated!

Software Goals

Only two things basically:

  1. Make it time affordable for less-coder scientists (who know nothing about WfMS) to manage their data processing workflows

  2. Preserve all the model run history and share them along with the code files





A live demo site is available.


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.


This project is impossible without the support of several fantastic open source libraries.

d3.js - BSD 3-Clause

graph-creator - MIT License

bootstrap - MIT License

CodeMirror - MIT License

JQuery Terminal - MIT License