Geoweaver
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boost data pipeline's tangibility, enhance research productivity, reduce work anxiety
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.
Why choose Geoweaver?
- 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.
GeoWeaver is a community effort. Any contribution is welcome and greatly appreciated!
Software Goals
Only two things basically:
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Make it time affordable for less-coder scientists (who know nothing about WfMS) to manage their data processing workflows
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Preserve all the model run history and share them along with the code files
Installation
Upgrade
Tutorial
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Create and Manipulate Hosts
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Create and Run Processes
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Create, Run, and Export Workflows
Demo
A live demo site is available.
Citation
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.
Dependencies
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
Community
License
MIT