An Innovative Open Data-driven Approach for Improved Interpretation of Coverage Data at NASA JPL's PO.DAA
Abstract
Figuratively speaking, Scientific Datasets (SD) are shared by data producers in a multitude of shapes, sizes and flavors. Primarily however they exist as machine-independent manifestations supporting the creation, access, and sharing of array-oriented SD that can on occasion be spread across multiple files. Within the Earth Sciences, the most notable general examples include the HDF family, NetCDF, etc. with other formats such as GRIB being used pervasively within specific domains such as the Oceanographic, Atmospheric and Meteorological sciences. Such file formats contain Coverage Data e.g. a digital representation of some spatio-temporal phenomenon. A challenge for large data producers such as NASA and NOAA as well as consumers of coverage datasets (particularly surrounding visualization and interactive use within web clients) is that this is still not a straight-forward issue due to size, serialization and inherent complexity. Additionally existing data formats are either unsuitable for the Web (like netCDF files) or hard to interpret independently due to missing standard structures and metadata (e.g. the OPeNDAP protocol). Therefore alternative, Web friendly manifestations of such datasets are required.CoverageJSON is an emerging data format for publishing coverage data to the web in a web-friendly, way which fits in with the linked data publication paradigm hence lowering the barrier for interpretation by consumers via mobile devices and client applications, etc. as well as data producers who can build next generation Web friendly Web services around datasets. This work will detail how CoverageJSON is being evaluated at NASA JPL's PO.DAAC as an enabling data representation format for publishing SD as Linked Open Data embedded within SD landing pages as well as via semantic data repositories. We are currently evaluating how utilization of CoverageJSON within SD landing pages addresses the long-standing acknowledgement that SD producers are not currently addressing content-based optimization within their SD landing pages for better crawlability by commercial search engines.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFMIN41B1660M
- Keywords:
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- 1916 Data and information discovery;
- INFORMATICSDE: 1920 Emerging informatics technologies;
- INFORMATICSDE: 1930 Data and information governance;
- INFORMATICSDE: 1950 Metadata: Quality;
- INFORMATICS