HydroShare: A Platform for Collaborative Data and Model Sharing in Hydrology
|Authors:||David Tarboton Ray Idaszak Jeffery S. Horsburgh Dan Ames Jonathan Goodall Alva Lind Couch Richard Hooper Pabitra Dash Michael J. Stealey Hong Yi Christina Bandaragoda Anthony Michael Castronova HydroShare Development Team|
|Resource type:||Composite Resource|
|Storage:||The size of this resource is 4.8 MB|
|Created:||Dec 08, 2017 at 5:10 a.m.|
|Last updated:||Dec 08, 2017 at 5:20 p.m. by David Tarboton|
|Citation:||See how to cite this resource|
HydroShare is an online, collaboration system for sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around “resources” which are defined by standardized content types for data formats and models commonly used in hydrology. With HydroShare you can: Share your data and models with colleagues; Manage who has access to the content that you share; Share, access, visualize and manipulate a broad set of hydrologic data types and models; Use the web services application programming interface (API) to program automated and client access; Publish data and models and obtain a citable digital object identifier (DOI); Aggregate your resources into collections; Discover and access data and models published by others; Use web apps to visualize, analyze and run models on data in HydroShare. This presentation will describe the functionality and architecture of HydroShare highlighting its use as a virtual environment supporting education and research. HydroShare has components that support: (1) resource storage, (2) resource exploration, and (3) web apps for actions on resources. The HydroShare data discovery, sharing and publishing functions as well as HydroShare web apps provide the capability to analyze data and execute models completely in the cloud (servers remote from the user) overcoming desktop platform limitations. The HydroShare GIS app provides a basic capability to visualize spatial data. The HydroShare JupyterHub Notebook app provides flexible and documentable execution of Python code snippets for analysis and modeling in a way that results can be shared among HydroShare users and groups to support research collaboration and education. We will discuss how these developments can be used to support different types of educational efforts in Hydrology where being completely web based is of value in an educational setting as students can all have access to the same functionality regardless of their computer.
Plain Language Summary
HydroShare is a web based hydrologic information system designed to enhance collaboration within the hydrology community through data sharing. Advancing hydrologic understanding requires combining information from multiple sources which requires collaboration and working as a team or community. HydroShare is a computer system that supports this by enabling users to share units of content referred to as “resources” that hold either data or hydrologic computer models in standardized formats. This presentation will describe the HydroShare data discovery, sharing and publishing capability as well how web apps (computer programs accessed through a web browser) can be used with HydroShare to analyze data and run models completely in servers remote from the user overcoming local desktop computer limitations.
Tarboton, D. G., R. Idaszak, J. S. Horsburgh, D. P. Ames, J. L. Goodall, A. Couch, R. P. Hooper, P. K. Dash, M. Stealey, H. Yi, T. Gan, C. Bandaragoda, A. M. Castronova and The HydroShare Development Team, (2017), "HydroShare: A Platform for Collaborative Data and Model Sharing in Hydrology," Abstract ED23D-0330 presented at 2017 Fall Meeting, AGU, New Orleans, Mississippi., 11-15 Dec, https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/298917.
|This resource cites:||Tarboton, D. G., R. Idaszak, J. S. Horsburgh, D. P. Ames, J. L. Goodall, A. Couch, R. P. Hooper, P. K. Dash, M. Stealey, H. Yi, C. Bandaragoda, A. M. Castronova and The HydroShare Development Team, (2017), "HydroShare: A Platform for Collaborative Data and Model Sharing in Hydrology," Abstract ED23D-0330 presented at 2017 Fall Meeting, AGU, New Orleans, Mississippi., 11-15 Dec, https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/298917.|
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|National Science Foundation||Collaborative Research: SI2-SSI: Cyberinfrastructure for Advancing Hydrologic Knowledge through Collaborative Integration of Data Science, Modeling and Analysis||1664061|
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