IN33B-1800
Curating Virtual Data Collections

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Christopher Lynnes, NASA Goddard Space Flight Center, Greenbelt, MD, United States, Hampapuram Ramapriyan, Science Systems and Applications, Inc., Lanham, MD, United States, Amanda Leon, National Snow and Ice Data Center, Boulder, CO, United States, Vardis M Tsontos, NASA Jet Propulsion Laboratory, Pasadena, CA, United States and Zhong Liu, George Mason University Fairfax, Center for Spatial Information Science and Systems (CSISS), Fairfax, VA, United States
Abstract:
NASA’s Earth Observing System Data and Information System (EOSDIS) contains a rich set of datasets and related services throughout its many elements. As a result, locating all the EOSDIS data and related resources relevant to particular science theme can be daunting. This is largely because EOSDIS data's organizing principle is affected more by the way they are produced than around the expected end use.

Virtual collections oriented around science themes can overcome this by presenting collections of data and related resources that are organized around the user's interest, not around the way the data were produced. Science themes can be:

  1. Specific applications (uses) of the data, e.g., landslide prediction
  2. Geophysical events (e.g., Hurricane Sandy)
  3. A specific science research problem

Virtual collections consist of annotated web addresses (URLs) that point to data and related resource addresses, thus avoiding the need to copy all of the relevant data to a single place. These URL addresses can be consumed by a variety of clients, ranging from basic URL downloaders (wget, curl) and web browsers to sophisticated data analysis programs such as the Integrated Data Viewer. Eligible resources include anything accessible via URL:

  1. data files: data file URLs
  2. data subsets: OPeNDAP, webification or Web Coverage Service URLs
  3. data visualizations: Web Map Service
  4. data search results: OpenSearch Atom response 
  5. custom analysis workflows: e.g., Giovanni analysis URL
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