Advancing Discovery and Usability of Operational-Ready Satellite Oceanographic Big Data within a NASA WDS-Trusted Repository

David F Moroni1, Edward M Armstrong1, John Charles Klose2, Suresh Vannan1, Jessica Hausman1 and Catalina M Oaida1, (1)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (2)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
NASA’s Physical Oceanography Distributed Active Archive Center has made tremendous progress in supporting operational-ready data, thus improving the Findability, Accessibility, Interoperability and Re-usability (FAIR) of its satellite data, in which over 500 datasets are publicly distributed and discoverable; 74 of these are near-real-time (NRT). These datasets cover a wide variety of parameters, such as ocean surface wind speed, sea surface temperature, ocean surface salinity, sea ice, ocean surface topography, ocean surface currents and ocean wave spectra. PO.DAAC is recognized as a community leader in addressing a wide range of Big Data challenges, receiving the CoreTrustSeal by the World Data System as a Trusted Repository, all while addressing FAIR data principles. This presentation will focus on the motivations, current implementations, and planned deployments supporting oceanographic data to both sustain and advance the operational use of current and future data sources. New opportunities for operational and science data users are enabled by cloud architecture, much of which is being developed by PO.DAAC: cloud-based and on-demand data analysis/visualization/GIS tools and services, virtual machine environments to support legacy analysis software and toolkits, open-source and web-based development environments, open-source code sharing, APIs for interactive data/metadata search and extraction, and an overall more consistent user experience in data tools/services. Additional headway has already been made toward frameworks and services that extend the operational readiness of data: 1) web services REST APIs for data granule search, subsetting and extraction, 2) web services toolkits and data recipes, 3) HTTPS-based WebDAV virtual drive mounting, 4) REST APIs for visualization and analytics, 5) interoperable data/metadata formats and metadata specifications 6) leveraging compression capabilities for increased I/O performance, 7) improved commercial and 3rd party data searching through JSON-LD tagging, 8) web-based documentation, and 9) open-source licensing of user-oriented software and tools. Pre-phase-E preparations for Surface Water Ocean Topography and Sentinel-6 missions are among the examples presented for cloud-based applications.