The National Center for Atmospheric Research (NCAR) Research Data Archive: a Data Education Center

Abstract:

The National Center for Atmospheric Research (NCAR) Research Data Archive (RDA), rda.ucar.edu, is not just another data center or data archive. It is a data education center. We not only serve data, we TEACH data.

Weather and climate data is the original “Big Data” dataset and lessons learned while playing with weather data are applicable to a wide range of data investigations. Erroneous data assumptions are the Achilles heel of Big Data. It doesn’t matter how much data you crunch if the data is not what you think it is.

Each dataset archived at the RDA is assigned to a data specialist (DS) who curates the data. If a user has a question not answered in the dataset information web pages, they can call or email a skilled DS for further clarification. The RDA’s diverse staff—with academic training in meteorology, oceanography, engineering (electrical, civil, ocean and database), mathematics, physics, chemistry and information science—means we likely have someone who “speaks your language.”

Data discovery is another difficult Big Data problem; one can only solve problems with data if one can find the right data. Metadata, both machine and human-generated, underpin the RDA data search tools. Users can quickly find datasets by name or dataset ID number. They can also perform a faceted search that successively narrows the options by user requirements or simply kick off an indexed search with a few words.

Weather data formats can be difficult to read for non-expert users; it’s usually packed in binary formats requiring specialized software and parameter names use specialized vocabularies. DSs create detailed information pages for each dataset and maintain lists of helpful software, documentation and links of information around the web.

We further grow the level of sophistication of the users with tips, tutorials and data stories on the RDA Blog, http://ncarrda.blogspot.com/. How-to video tutorials are also posted on the NCAR Computational and Information Systems Laboratory (CISL) YouTube channel.