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International Congress on Environmental Modelling and Software

Conference

2018

HydroShare

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Using Hydroshare To Enhance Sharing And Reproducibility Of Research Results, Jeffery S. Horsburgh, David Tarboton, Anthony M. Castronova, Jonathan L. Goodall Jun 2018

Using Hydroshare To Enhance Sharing And Reproducibility Of Research Results, Jeffery S. Horsburgh, David Tarboton, Anthony M. Castronova, Jonathan L. Goodall

International Congress on Environmental Modelling and Software

Abstract: HydroShare is a web-based hydrologic information system operated by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI). Within HydroShare, users can create and share data and models using a variety of file formats and flexible metadata. HydroShare enables users to formally publish these resources as well as create linkages between published data and model resources and peer reviewed journal publications that describe them. Ability to link published data and models with the papers that describe them is a great step in the direction of scientific reproducibility, but is only a first step. HydroShare supports further …


Automated Data Discovery, Retrieval, Manipulation, And Publication Using Python, Tethys, And Hydroshare, Scott D. Christensen, Dharhas Pothina, Aaron Valoroso, Kevin Winters Jun 2018

Automated Data Discovery, Retrieval, Manipulation, And Publication Using Python, Tethys, And Hydroshare, Scott D. Christensen, Dharhas Pothina, Aaron Valoroso, Kevin Winters

International Congress on Environmental Modelling and Software

Most environmental modelling efforts have significant data needs, which can present technical challenges and distract from the primary modelling objectives. These challenges include finding relevant data sources, retrieving large amounts of data, performing data transformations, and finally storing and sharing results. This presentation describes the tools being used and developed at the U.S. Army Engineer Research and Development Center (ERDC) to address these challenges. These tools include (1) Quest, an extensible Python library for searching various local and public data providers, automating downloading, performing various data filters (or transformations), and finally, publishing the data to data repositories, (2) Data Depot, …