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

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.