Armstrong, E. M., Bourassa, M. A., Cram, T. A., DeBellis, M., Elya, J., Greguska III, F. R., et al. (2019). An Integrated Data Analytics Platform. Front. Mar. Sci. , 6 , 354.
Abstract: An Integrated Science Data Analytics Platform is an environment that enables the confluence of resources for scientific investigation. It harmonizes data, tools and computational resources to enable the research community to focus on the investigation rather than spending time on security, data preparation, management, etc. OceanWorks is a NASA technology integration project to establish a cloud-based Integrated Ocean Science Data Analytics Platform for big ocean science at NASA’s Physical Oceanography Distributed Active Archive Center (PO.DAAC) for big ocean science. It focuses on advancement and maturity by bringing together several NASA open-source, big data projects for parallel analytics, anomaly detection, in situ to satellite data matchup, quality-screened data subsetting, search relevancy, and data discovery. Our communities are relying on data available through distributed data centers to conduct their research. In typical investigations, scientists would (1) search for data, (2) evaluate the relevance of that data, (3) download it, and (4) then apply algorithms to identify trends, anomalies, or other attributes of the data. Such a workflow cannot scale if the research involves a massive amount of data or multi-variate measurements. With the upcoming NASA Surface Water and Ocean Topography (SWOT) mission expected to produce over 20PB of observational data during its 3-year nominal mission, the volume of data will challenge all existing Earth Science data archival, distribution and analysis paradigms. This paper discusses how OceanWorks enhances the analysis of physical ocean data where the computation is done on an elastic cloud platform next to the archive to deliver fast, web-accessible services for working with oceanographic measurements.
Banks, R. F., Bourassa, M. A., Hughes, P., O'Brien, J. J., & Smith, S. R. (2006). Variability of surface turbulent fluxes over the Indian Ocean. In 14th Conference on Interactions of the Sea and Atmosphere (cdrom).
Bentamy, A., Piollé, J. F., Grouazel, A., Danielson, R., Gulev, S., Paul, F., et al. (2017). Review and assessment of latent and sensible heat flux accuracy over the global oceans. Remote Sensing of Environment , 201 , 196–218.
Bourassa, M. A. (2009). Uncertainty in scatterometer derived vorticity. In 2009 IEEE International Geoscience and Remote Sensing Symposium (III-pp. 805– III-808).
Bourassa, M. A. (2009). The future of wind measurements from space. Space News , (Nov. 23), 2.
Bourassa, M. A. (2006). Satellite-based observations of surface turbulent stress during severe weather. Atmosphere-Ocean Interactions , 2 , 35–52.
Bourassa, M. A. (2004). A Sea Surface Stress Parameterization Dependent on Directional Seastate. In CAS/JSC Working Group on Numerical Experimentation, Research Activities in Atmospheric and Oceanic Modeling (4.pp. 07–4.08). Geneva, Switzerland: World Meteorological Organization.
Bourassa, M. A. (2001). Tehuantepec wind and pressure changes associated with tropical cyclones. In 11th Conference on Interactions of the Sea and Atmosphere, Amer. Meteor. Soc., San Diego, CA, USA (pp. 27–28).
Bourassa, M. A., D. Dukhovskoy, S. L. Morey, and J, J. O'Brien. (2007). Innovations in Modeling Gulf of Mexico Surface Turbulent Fluxes. Flux News , (3), 9.
Bourassa, M. A., H. Bonekamp, P. Chang, D. Chelton, J. Courtney, R. Edson, J. Figa, Y. He, H. Hersbach, K. Hilburn, Z. Jelenak, T. Lee, W. T. Liu, D. Long, K. Kelly, R. Knabb, E. Lindstorm, W. Perrie, M. Portabella, M. Powell, E. Rodriguez, D. Smith, A. Stoffelen, V. Swail, F. Wentz. (2010). Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling. In D. D.E. and Stammer Harrison J. Hall (Ed.), Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2).