https://github.com/esipfed/open-data-education
Open Science Education - Pangeo
https://github.com/esipfed/open-data-education
esip-lab pangeo
Last synced: 10 months ago
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Open Science Education - Pangeo
- Host: GitHub
- URL: https://github.com/esipfed/open-data-education
- Owner: ESIPFed
- Created: 2020-06-18T22:46:03.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2021-04-20T22:31:35.000Z (about 5 years ago)
- Last Synced: 2024-06-11T16:54:05.961Z (about 2 years ago)
- Topics: esip-lab, pangeo
- Language: Jupyter Notebook
- Homepage:
- Size: 12.4 MB
- Stars: 5
- Watchers: 6
- Forks: 3
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Building Pathways for Open Science Education using NASA datasets
[](https://mybinder.org/v2/gh/ESIPFed/open-data-education/master?urlpath=lab)
[](https://travis-ci.org/ESIPFed/open-data-education)
## Introduction
Here we will create a hypothetical scientific use case: A user wants to use the cloud to analyze change in landcover over a certain region in the Amazon river basin over a period of 20 years. The goal of this tutorial then is to introduce users to working with NASA satellite imagery and utilizing Amazon Web Services' Open Data program. Through a series of standardized modules, the user is shown an end-to-end workflow for working with satellite imagery. The modules will teach users how to utilize geoscientific Python tools, visualize the data and utilize a parallel computation platform on the cloud (i.e. the Pangeo Platform).
## Description
The contents of this repository consists of a series of Jupyter Notebooks and can be viewed on an open source, free computational platform like Binder. To view the contents of this repo, click the launch binder icon above.
## Prerequisites
We encourage users to have basic knowledge of Python and Git. The [Software Carpentry](https://swcarpentry.github.io/) education materials is a great place to start.
## Tutorial index
|Name |Description|link|
|-----|-----------|----|
|Introduction to Cloud Computing|Working with Big Data |[Tutorial 1](/01_intro_to_cloud.ipynb) |
|AWS Open datasets |Working with s3 buckets | [Tutorial 2](/02_aws_opendatasets.ipynb) |
|Multi-dimensional analysis | Introduction to Xarray | [Tutorial 3](/03_multidim_analysis.ipynb) |
|Parallel Computing |Introduction to Dask | [Tutorial 4](/04_parallel_computing.ipynb) |
|Visualization |Introduction to HoloViews | [Tutorial 5](/05_data_visualization.ipynb) |
|Scaling-up |Using Dask and Pangeo | [Tutorial 6](/06_scalingup_pangeo.ipynb) |
## Issues/Collaboration
**Feedback/new tutotrial**
You can request new content or give general feedback through Gitub issues or collaborate on these materials by creating a Pull Request.
## Acknowledgements
The contents of this repository was developed by Aji John and Amanda Tan at the University of Washington with funding from the ESIPLab Summer 2020 Incubator Award 2020.
```python
```