Collaborative Sharing of Multidimensional Space-tie Data Using HydroShare

Document Type

Presentation

Location

Tuscaloosa, Alabama

Publication Date

1-1-2015

Abstract

HydroShare is a collaborative environment being developed for sharing hydrological data and models. It includes capability to upload data in many formats as resources that can be shared. The HydroShare data model for resources uses a specific format for the representation of each type of data and specifies metadata common to all resource types as well as metadata unique to specific resource types. The Network Common Data Form (NetCDF) was chosen as the format for multidimensional space-time data in HydroShare. NetCDF is widely used in hydrological and other geoscience modeling because it contains self-describing metadata and supports the creation of array-oriented datasets that may include three spatial dimensions, a time dimension and other user defined dimensions. For example, NetCDF may be used to represent precipitation or surface air temperature fields that have two dimensions in space and one dimension in time. This presentation will illustrate how NetCDF files are used in HydroShare. When a NetCDF file is loaded into HydroShare, header information is extracted using the "ncdump" utility. Python functions developed for the Django web framework on which HydroShare is based, extract science metadata present in the NetCDF file, saving the user from having to enter it. Where the file follows Climate Forecast (CF) convention and Attribute Convention for Dataset Discovery (ACDD) standards, metadata is thus automatically populated. Users also have the ability to add metadata to the resource that may not have been present in the original NetCDF file. HydroShare's metadata editing functionality then writes this science metadata back into the NetCDF file to maintain consistency between the science metadata in HydroShare and the metadata in the NetCDF file. This further helps researchers easily add metadata information following the CF and ACDD conventions. Additional data inspection and subsetting functions were developed, taking advantage of Python and command line libraries for working with NetCDF files. We describe the design and implementation of these features and illustrate how NetCDF files from a modeling application may be curated in HydroShare and thus enhance reproducibility of the associated research. We also discuss future development planned for multidimensional space-time data in HydroShare.

Comments

3rd CUAHSI Conference on Hydroinformatics, University of Alabama & the National Water Center

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