Skip to main content
Skip to main content

COAPS Virtual Library (Publications)

Search within Results:
Display Options:

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author (up) Armstrong, E. M.; Bourassa, M. A.; Cram, T.; Elya, J. L.; Greguska, F. R., III; Huang, T.; Jacob, J. C.; Ji, Z.; Jiang, Y.; Li, Y.; McGibbney, L. J.; Quach, N.; Smith, S. R.; Tsontos, V. M.; Wilson, B. D.; Worley, S. J.; Yang, C. P. url  openurl
  Title An information technology foundation for fostering interdisciplinary oceanographic research and analysis Type $loc['typeAbstract']
  Year 2018 Publication American Geophysical Union Abbreviated Journal AGU  
  Volume Fall Meeting Issue Pages  
  Keywords 1914 Data mining, INFORMATICSDE: 4805 Biogeochemical cycles, processes, and modeling, OCEANOGRAPHY: BIOLOGICAL AND CHEMICALDE: 4273 Physical and biogeochemical interactions, OCEANOGRAPHY: GENERALDE: 4504 Air/sea interactions, OCEANOGRAPHY: PHYSICAL  
  Abstract Before complex analysis of oceanographic or any earth science data can occur, it must be placed in the proper domain of computing and software resources. In the past this was nearly always the scientist's personal computer or institutional computer servers. The problem with this approach is that it is necessary to bring the data products directly to these compute resources leading to large data transfers and storage requirements especially for high volume satellite or model datasets. In this presentation we will present a new technological solution under development and implementation at the NASA Jet Propulsion Laboratory for conducting oceanographic and related research based on satellite data and other sources. Fundamentally, our approach for satellite resources is to tile (partition) the data inputs into cloud-optimized and computation friendly databases that allow distributed computing resources to perform on demand and server-side computation and data analytics. This technology, known as NEXUS, has already been implemented in several existing NASA data portals to support oceanographic, sea-level, and gravity data time series analysis with capabilities to output time-average maps, correlation maps, Hovmöller plots, climatological averages and more. A further extension of this technology will integrate ocean in situ observations, event-based data discovery (e.g., natural disasters), data quality screening and additional capabilities. This particular activity is an open source project known as the Apache Science Data Analytics Platform (SDAP) (https://sdap.apache.org), and colloquially as OceanWorks, and is funded by the NASA AIST program. It harmonizes data, tools and computational resources for the researcher allowing them to focus on research results and hypothesis testing, and not be concerned with security, data preparation and management. We will present a few oceanographic and interdisciplinary use cases demonstrating the capabilities for characterizing regional sea-level rise, sea surface temperature anomalies, and ocean hurricane responses.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ user @ Serial 1004  
Permanent link to this record
 

 
Author (up) Armstrong, E.M.; Bourassa, M.A.; Cram, T.A.; DeBellis, M.; Elya, J.; Greguska III, F.R.; Huang, T.; Jacob, J.C.; Ji, Z.; Jiang, Y.; Li, Y.; Quach, N.; McGibbney, L.; Smith, S.; Tsontos, V.M.; Wilson, B.; Worley, S.J.; Yang, C.; Yam, E. url  doi
openurl 
  Title An Integrated Data Analytics Platform Type $loc['typeJournal Article']
  Year 2019 Publication Frontiers in Marine Science Abbreviated Journal Front. Mar. Sci.  
  Volume 6 Issue Pages 354  
  Keywords  
  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.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2296-7745 ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ user @ Serial 1042  
Permanent link to this record
 

 
Author (up) Huang, T.; Armstrong, E.M.; Bourassa, M.A.; Cram, T.A.; Elya, J.; Greguska, F.; Jacob, J.C.; Ji, Z.; Jiang, Y.; Li, Y.; Quach, N.T.; McGibbney, L.J.; Smith, S.R.; Wilson, B.D.; Worley S.J.; Yang, C. url  doi
openurl 
  Title An Integrated Data Analytics Platform Type $loc['typeJournal Article']
  Year 2019 Publication Marine Science Abbreviated Journal Mar. Sci.  
  Volume 6 Issue Pages  
  Keywords big data, Cloud computing, Ocean science, data analysis, Matchup, anomaly detection, open source  
  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.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ user @ Serial 1038  
Permanent link to this record
 

 
Author (up) Jacob, J. C.; Armstrong, E. M.; Bourassa, M. A.; Cram, T.; Elya, J. L.; Greguska, F. R., III; Huang, T.; Ji, Z.; Jiang, Y.; Li, Y.; McGibbney, L. J.; Quach, N.; Smith, S. R.; Tsontos, V. M.; Wilson, B. D.; Worley, S. J.; Yang, C. P. url  openurl
  Title OceanWorks: Enabling Interactive Oceanographic Analysis in the Cloud with Multivariate Data Type $loc['typeAbstract']
  Year 2018 Publication American Geophysical Union Abbreviated Journal AGU  
  Volume Fall Meeting Issue Pages  
  Keywords 910 Data assimilation, integration and fusion, INFORMATICSDE: 1916 Data and information discovery, INFORMATICSDE: 1926 Geospatial, INFORMATICSDE: 1942 Machine learning, INFORMATICS  
  Abstract NASA's Advanced Information System Technology (AIST) Program sponsors the OceanWorks project to establish an integrated data analytics center at the Physical Oceanography Distributed Active Archive Center (PO.DAAC). OceanWorks provides a series of interoperable capabilities that are essential for cloud-scale oceanographic research. These include big data analytics, data search with subsecond response, intelligent ranking of search results, subsetting based on data quality metrics, and rapid spatiotemporal matchup of satellite measurements with distributed in situ data. The software behind OceanWorks is being developed as an open source project in the Apache Incubator Science Data Analytics Platform (SDAP – http://sdap.apache.org). In this presentation we describe how OceanWorks enables efficient, scalable, interactive and interdisciplinary oceanographic analysis with multivariate data.

Interactivity is enabled by a number of SDAP features. First, SDAP provides Representational State Transfer (REST) interfaces to a number of built-in cloud analytics to compute time series, time-averaged maps, correlation maps, climatological maps, Hovmöller maps, and more. To access these, users simply navigate to a properly constructed parameterized URL in their web browser or issue web services calls in a variety of programming languages or in a Jupyter notebook. Alternatively, Python clients can make function calls via the NEXUS Command Line Interface (CLI). Authenticated users can even inject their own custom code via REST calls or the CLI.

To enable interdisciplinary science, OceanWorks provides access to a rich collection of multivariate satellite and in situ measurements of the oceans (e.g., sea surface temperature, height and salinity, chlorophyll and circulation) and other Earth science data (e.g., aerosol optical depth and wind speed), coupled with on-demand processing capabilities close to the data. We partition the data across space or time into tiles and store them into cloud-aware databases that are collocated with the computations. We will provide examples of scientific studies directly enabled by OceanWorks' multivariate data and cloud analytics.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ user @ Serial 1005  
Permanent link to this record
 

 
Author (up) O'hara, S. H.; Arko, R. A.; Clark, D.; Chandler, C. L.; Elya, J. L.; Ferrini, V. L.; McLain, K.; Olson, C. J.; Sellers, C. J.; Smith, S. R.; Stocks, K. I.; Stolp, L.; Carbotte, S. M. openurl 
  Title Rolling Deck to Repository (R2R) Program Data Services for the Oceanographic Research Community Type $loc['typeJournal Article']
  Year 2018 Publication American Geophysical Union Abbreviated Journal  
  Volume Issue Pages  
  Keywords 4299 General or miscellaneous, OCEANOGRAPHY: GENERAL  
  Abstract Research vessels supported by NSF are critical platforms contributing to academic oceanographic research in the US. The “underway” data sets obtained from the continuously operating geophysical, water column, and meteorological sensors aboard these vessels provide characterization of basic environmental conditions for the oceans and are of high scientific value for building global syntheses, climatologies, and historical time series of ocean properties (e.g the World Ocean Atlas, the GMRT bathymetric synthesis, ICOADS). The Rolling deck to Repository program (www.rvdata.us) provides a central shore-side data gateway that ensures the basic documentation, assessment and submission of all environmental data from ship operators to the NOAA long-term archives for these data.

R2R provides a set of data services for the oceanographic research community, including: publishing an online, searchable and browsable master cruise catalog, supported by cruise and data set DOIs; organizing, archiving, and disseminating original underway data and documents; assessing data quality on select data types; creating select post-field data products; and supporting at-sea event logging.

In this presentation we will discuss new developments in R2R data services and challenges associated with ship-based data management. A significant challenge is the dramatic increase in data volumes associated with new sensors (e.g. the EK80 Sonar systems) whereby individual cruise distributions can be several terabytes. Ship operators, R2R and NCEI must design a way to move and store these growing volumes. R2R is also working to make information more accessible and complete. A new website has been launched along with API web services that allow users to find and use data more easily. R2R is working to improve device metadata, including working to identify the time sources for all environmental sensors to support accurate comparison and merging of data sets.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ user @ Serial 1006  
Permanent link to this record
 

 
Author (up) O'hara, S. H.; Arko, R. A.; Clark, D.; Chandler, C. L.; Elya, J. L.; Ferrini, V. L.; McLain, K.; Olson, C. J.; Sellers, C. J.; Smith, S. R.; Stocks, K. I.; Stolp, L.; Carbotte, S. M. url  openurl
  Title Rolling Deck to Repository (R2R) Program Data Services for the Oceanographic Research Community Type $loc['typeAbstract']
  Year 2018 Publication American Geophysical Union Abbreviated Journal AGU  
  Volume American Geophysical Union, Fall Meeting 2018 Issue Pages  
  Keywords OCEANOGRAPHY: GENERAL  
  Abstract Research vessels supported by NSF are critical platforms contributing to academic oceanographic research in the US. The “underway” data sets obtained from the continuously operating geophysical, water column, and meteorological sensors aboard these vessels provide characterization of basic environmental conditions for the oceans and are of high scientific value for building global syntheses, climatologies, and historical time series of ocean properties (e.g the World Ocean Atlas, the GMRT bathymetric synthesis, ICOADS). The Rolling deck to Repository program (www.rvdata.us) provides a central shore-side data gateway that ensures the basic documentation, assessment and submission of all environmental data from ship operators to the NOAA long-term archives for these data. R2R provides a set of data services for the oceanographic research community, including: publishing an online, searchable and browsable master cruise catalog, supported by cruise and data set DOIs; organizing, archiving, and disseminating original underway data and documents; assessing data quality on select data types; creating select post-field data products; and supporting at-sea event logging. In this presentation we will discuss new developments in R2R data services and challenges associated with ship-based data management. A significant challenge is the dramatic increase in data volumes associated with new sensors (e.g. the EK80 Sonar systems) whereby individual cruise distributions can be several terabytes. Ship operators, R2R and NCEI must design a way to move and store these growing volumes. R2R is also working to make information more accessible and complete. A new website has been launched along with API web services that allow users to find and use data more easily. R2R is working to improve device metadata, including working to identify the time sources for all environmental sensors to support accurate comparison and merging of data sets.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ user @ Serial 1020  
Permanent link to this record
 

 
Author (up) Smith, S.R.; Briggs, K.; Bourassa, M.A.; Elya, J.; Paver, C.R. url  doi
openurl 
  Title Shipboard automated meteorological and oceanographic system data archive: 2005-2017 Type $loc['typeJournal Article']
  Year 2018 Publication Geoscience Data Journal Abbreviated Journal Geosci Data J  
  Volume 5 Issue 2 Pages 73-86  
  Keywords data stewardship; marine meteorology; open data access; quality control; thermosalinograph  
  Abstract Since 2005, the Shipboard Automated Meteorological and Oceanographic System (SAMOS) initiative has been collecting, quality-evaluating, distributing, and archiving underway navigational, meteorological, and oceanographic observations from research vessels. Herein we describe the procedures for acquiring ship and instrumental metadata and the one-minute interval observations from 44 research vessels that have contributed to the SAMOS initiative from 2005 to 2017. The overall data processing workflow and quality control procedures are documented along with data file formats and version control procedures. The SAMOS data are disseminated to the user community via web, FTP, and Thematic Real-time Environmental Distributed Data Services from both the Marine Data Center at the Florida State University and the National Centers for Environmental Information, which serves as the long-term archive for the SAMOS initiative. They have been used to address topics ranging from air-sea interaction studies, the calibration, evaluation, and development of satellite observational products, the evaluation of numerical atmospheric and ocean models, and the development of new tools and techniques for geospatial data analysis in the informatics community. Maps provide users the geospatial coverage within the SAMOS dataset, with a focus on the Essential Climate/Ocean Variables, and recommendations are made regarding which versions of the dataset should be accessed by different user communities.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2049-6060 ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ rl18 @ Serial 979  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records:

2000 Levy Avenue
Building A, Suite 292
Tallahassee, FL 32306-2741
Phone: (850) 644-4581
Fax: (850) 644-4841
contact@coaps.fsu.edu

© 2021 Center for Ocean-Atmospheric Prediction Studies (COAPS), Florida State University

Center for Ocean-Atmospheric Prediction Studies (COAPS)