HydroShare: A Platform for Open Water Data

Presentation at AWRA National Conference in Salt Lake City. November 4, 2019.

HydroShare (www.hydroshare.org) is a hydrology-domain specific data and model repository operated by the Consortium of Universities for the Advancement of Hydrologic Science Inc. (CUAHSI). HydroShare’s goal is to advance hydrologic science by enabling researchers to more easily share data, model and workflow products resulting from their research, creating and supporting reproducibility of the results reported in scientific publications. It supports the growing call for open data that is findable, accessible, interoperable and reusable (FAIR). HydroShare is comprised of two sets of functionality: (1) a repository for users to share and publish data and models, collectively referred to as resources, in a variety of formats, and (2) web application tools that can act on content in HydroShare for computational and visual analysis. Together these serve as a platform for collaboration and gateway for computation that integrates data storage, organization, discovery, and analysis and that allows researchers to employ services beyond their desktop computers to make data storage and manipulation more reliable and scalable, while improving their ability to collaborate and reproduce results. This presentation will describe ongoing enhancements to HydroShare and some of the challenges being faced in its design and ongoing development. We report on efforts to refine the way data and model content are formatted and stored within the system to better support storage, management, and sharing of the diverse data involved with hydrologic data and model studies. We have developed techniques that enable scientists to organize and package data and models within a single shareable unit, while still providing value-added tools for known data types. Additionally, access to reproducible and easy to use computational functionality is being advanced using JupyterHub as a gateway to computing resources. This collaborative and computational functionality provides an important incentive by providing users with immediate value, while meeting open data mandates and sharing data using open standards.