Building and Validating Multidimensional Datasets in Hydrology for Data and Mapping Web Service Compliance

Multidimensional, georeferenced data are used extensively in hydrology, meteorology, and water science engineering. These produced, shared, by diverse organizations globally. Conventions have been developed to standardize the metadata format of these datasets ensure compatibility with current future software web services. However, most common conventions complex difficult implement correctly, resulting that unusable for many applications due a lack compliance conventions. We method module programmatically assigning guiding dataset creation, validating, cleaning process, so convention-compliant can be consistently repeatably created people limited knowledge file formats standards. then any application supports particular standard. Specifically, this paper examines process building multidimensional, netCDF compliant NetCDF Climate Forecast Conventions. present new free open-source Python package called cfbuild helps automate or updating datasets, making them sufficiently Attribute Data Discovery they reliably served using THREDDS Server shared via OPeNDAP.