Presentation IN32A-02 at 2019 AGU Fall Meeting, San Francisco, CA, December 11, https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/579336.

Tarboton, D. G., R. Idaszak, J. S. Horsburgh, D. P. Ames, J. L. Goodall, A. Couch, P. K. Dash, H. Yi, C. Bandaragoda, A. M. Castronova, R. Hooper, S. Wang, M. Ramirez, J. Sadler, M. Morsy, S. Black, C. Calloway, J. Bales and The HydroShare Development Team, (2019), "Advances in the HydroShare Community Platform Enabling the Integration of Water Data in Support of Hydrologic Research," Presentation IN32A-02 at 2019 AGU Fall Meeting, San Francisco, CA, 9-13 Dec. https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/579336.

Plain Language Summary

HydroShare is a domain specific data and model repository operated by the Consortium of Universities for the Advancement of Hydrologic Science Inc. (CUAHSI) to advance hydrologic science by enabling individual researchers to more easily and freely share products resulting from their research, not just the scientific publication summarizing a study, but also the data and models used to create the scientific publication. HydroShare accepts data from anybody, and supports Findable, Accessible, Interoperable and Reusable (FAIR) principles. It is comprised of two sets of functionalities: (1) a repository for users to share and publish data and models in a variety of formats, and (2) tools (web apps) that can act on content in HydroShare and support web-based access to compute capability. Together these move us towards a platform for collaboration and computation that integrates data storage, organization, discovery, and analysis through web applications (web apps) and that allows researchers to employ services beyond the desktop to make data storage and manipulation more reliable and scalable, while improving their ability to collaborate and reproduce results. This presentation will describe advances in the tools, methods and practices for data and model publication implemented in HydroShare.

Full Abstract

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 functionalities: (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, interoperability with computational tools such as JupyterHub that enable workflow reproducibility has been enhanced providing an easy to use 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.