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EDMW 2024 - Workshop 3B: Introduction to using earth data in the cloud for scientific workflows

Overview

Earth science data is increasingly available from the cloud and due to the size of many of these dataset (Tb and Pb in some cases), data workflows are transitioning to workflows that involve programmatic access with either cloud-native analysis or server-side processing . In this workshop, participants will take part in hands-on tutorials on working with earth data in the cloud with Python and/or R using a JupyterHub (cloud computing platform) provisioned for geospatial analysis. Participants will learn the basics of searching cloud resources via SpatioTemporal Asset Catalogs (STAC) and NASA Earth Data via Common Metadata Repository (CMR). Participants will go through tutorials to learn how to incorporate earth data into their science projects via cloud-native and server-side workflows. Participants will also be exposed to the Python and R suite of geospatial packages for gridded and other spatial data.

Aims and Objectives

  • Learn how to discover and use oceanographic remote-sensing data in NASA Earth Data
  • Familiarize participants with using remote-sensing data in R and Python with code.
  • Obtain hands-on experience in using remote-sensing data for two science applications.
  • Learn by doing and running through examples yourself.

What to expect

  • We will have short introductions and then will work through tutorials together. You are encouraged to adapt the code to create output and examples for your own data and areas of interest.

  • All tutorials and examples are developed openly and will be publicly available during and following the event. Participants will strengthen their practice of open science, using open source code and collaborating on their projects with course peers.

Disclaimer

This repository is a scientific product and is not official communication of the National Oceanic and Atmospheric Administration, or the United States Department of Commerce. All NOAA GitHub project content is provided on an ‘as is’ basis and the user assumes responsibility for its use. Any claims against the Department of Commerce or Department of Commerce bureaus stemming from the use of this GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.

License

This content was created by U.S. Government employees as part of their official duties. This content is not subject to copyright in the United States (17 U.S.C. §105) and is in the public domain within the United States of America. Additionally, copyright is waived worldwide through the CC0 1.0 Universal public domain dedication.