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WaterSciCon24 Workshop Materials: Advancing Open Data Science and Analytics for Water

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Created:	Apr 26, 2024 at 6:03 p.m.
Last updated:	Jul 30, 2024 at 11:06 p.m.
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Abstract

Water science and management challenges require synthesis of diverse data. Many data analysis tasks are difficult because data are large or complex; standard formats are not always agreed upon or mapped to efficient structures for analysis; scientists may lack training for tackling large and complex datasets; and it can be difficult to share, collaborate around, and reproduce scientific work. Access to computing for running and sharing data science or modeling workflows and structuring them in a way that they can be reproduced can also be challenging. Overcoming these barriers can transform the way water scientists work. Participants will learn how to use multiple data science tools, including data retrieval packages for easy access to data from the United States Geological Survey’s (USGS) National Water Information System (NWIS) and tools associated with the CUAHSI HydroShare repository and linked JupyterHub environment available to assist scientists in building, sharing, and publishing more reproducible scientific workflows following Findable, Accessible, Interoperable, and Reusable (FAIR) principles. We will demonstrate how the technical burden for scientists associated with creating a computational environment for executing analyses can be reduced and how sharing and reproducibility of analyses can be enhanced through the use of these tools.

This HydroShare resource includes all of the materials presented in a workshop at WaterSciCon24.

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readme.md

WaterSciCon24 Workshop Materials

This HydroShare resource contains the materials presented at the WaterSciCon24 conference held in Saint Paul, MN June 24-27, 2024.

Workshop Title: Advancing Open Data Science and Analytics for Water

Learning Objectives

After attending this workshop, participants will be able to:

Use the USGS data retrieval packages to retrieve and work with data from the USGS NWIS system.
Access geospatial data from the 3D elevation (3DEP) database and Reference Hydrologic Geospatial Fabric.
Use HydroShare’s client package to interact with the HydroShare repository to create resources, create and edit metadata, and share content.
Create and share executable Jupyter notebooks using these tools and the CUAHSI JupyterHub computational environment in support of developing FAIR computational workflows.

Preparing for the Workshop

Before executing the notebooks contained in this resource, participants must complete the following:

Create a HydroShare user account
Log in to HydroShare and request to join the CUAHSI Cloud Computing group at https://www.hydroshare.org/group/156

See the HydroShare Jupyter Quickstart PDF document in this resource if you need instructions.

Executing the Notebooks

To execute the interactive notebooks in this resource:

At the top of this page in HydroShare, click the "Open with" button and select "CUAHSI JupyterHub"
When prompted, select the first server option in the list of server options - "Python v3.9.7 - JupyterLab Interface"
Scroll to the bottom of the server options and click the "Start" button
Wait for your server to start up and then double click on the notebook you want to run in the file browser panel on the left.

Files Included in this Resource

Notebooks: Folder containing all of the example notebooks presented
Presentations: Folder containing all of the slides presented
HydroShareJupyterQuickstart.pdf: Instructions for getting access to the CUAHSI JupyterHub server through HydroShare

Additional Example Notebooks

See the "Related Resources" metadata section below for links to HydroShare resources containing additional example Jupyter notebooks demonstrating how to use the USGS dataretrieval Python package and the hsclient Python client package.

Related Resources

The content of this resource references	Chegini et al., (2021). HyRiver: Hydroclimate Data Retriever. Journal of Open Source Software, 6(66), 3175, https://doi.org/10.21105/joss.03175
The content of this resource references	Blodgett, D., Johnson, J.M., 2022, nhdplusTools: Tools for Accessing and Working with the NHDPlus, https://doi.org/10.5066/P97AS8JD
The content of this resource references	Horsburgh, J. S., A. S. Jones, S. S. Black, T. O. Hodson (2022). USGS dataretrieval Python Package Usage Examples, HydroShare, http://www.hydroshare.org/resource/c97c32ecf59b4dff90ef013030c54264
The content of this resource references	Horsburgh, J. S., S. S. Black (2021). HydroShare Python Client Library (hsclient) Usage Examples, HydroShare, http://www.hydroshare.org/resource/7561aa12fd824ebb8edbee05af19b910
The content of this resource references	Hodson, T. S., DeCicco, L. A., Hariharan, J. A., Stanish, L. F., Black, S., Horsburgh, J. S. (2023). Reproducibility Starts at the Source: R, Python, and Julia Packages for Retrieving USGS Hydrologic Data, Water, 15(24), 4236, https://doi.org/10.3390/w15244236.

Credits

Funding Agencies

This resource was created using funding from the following sources:

Agency Name	Award Title	Award Number
National Science Foundation	Collaborative Research: Elements: Advancing Data Science and Analytics for Water (DSAW)	1931297

How to Cite

Horsburgh, J. S., D. Blodgett, T. Hodson, A. M. Castronova, I. Garousi-Nejad, A. Jones, L. DeCicco, L. Stanish (2024). WaterSciCon24 Workshop Materials: Advancing Open Data Science and Analytics for Water, HydroShare, http://www.hydroshare.org/resource/c0184e9db2714782a03520ce1efde7ba

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/

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