OceanObs’09 Community White Paper Proposal

Coastal Data Management (tentative title)

Lead author:

Jeff de La Beaujardière

NOAA Integrated Ocean Observing System (IOOS) Program

1100 Wayne Ave #1225, Silver Spring MD 20901 USA

+1 301 427 2427

Corresponding authors:

OceanObs’09 Community White Paper Proposal

C. J. Beegle-Krause

Applied Science Associates, Inc.

10002 Aurora Ave N Ste 36, PMB 4401

Seattle, WA 98133USA

Luis Bermudez

Southeastern Univ. Research Assoc. (SURA)

1201 New York Ave. NW Suite 430, Washington DC 20005 USA

Steven Hankin

NOAA Pacific Marine Environment Lab (PMEL)

7600 Sand Point Way NE

Seattle, WA 98115 USA

Lisa Hazard

Southern California Coastal Ocean Observing System (SCCOOS) and Scripps Institution of Oceanography

9500 Gilman Drive M/C 0213

La Jolla, CA 92093 USA

Eoin Howlett

Mid-Atlantic Regional Coastal Ocean Observing System (MARCOOS)

55 Village Square Drive

South Kingstown, RI 02879 USA

Steven Le

Central and Northern California Ocean Observing System (CENCOOS)

1275 Columbus Ave

San Francisco, CA 94133 USA

Roger Proctor

Integrated Marine Observing System (IMOS)

University of Tasmania, Private Bag 110, Hobart TAS 7001 Australia

Richard P. Signell

USGS Coastal and Marine Geology Program

384 Woods Hole Rd.

Woods Hole, MA 02543 USA

Derrick Snowden

NOAA Climate Program Office, Climate Observation Division

1100 Wayne Avenue, Suite 1202

Silver Spring, MD 20910 USA

Julie Thomas

Southern California Coastal Ocean Observing System (SCCOOS) and Scripps Institution of Oceanography

9500 Gilman Drive M/C 0214

La Jolla, CA 92093 USA

OceanObs’09 Community White Paper Proposal


The US Integrated Ocean Observing System (IOOS®), its regional coastal ocean observing partners, and the Australian Integrated Marine Observation System propose to submit a Community White Paper to the OceanObs2009 conference. Topics to be considered include:

-  Data management consists primarily of the system (or network of systems) for publishing, acquisition, storage, registration and permanent archiving of data collections, The operations within a robust data management system should be tested, reliable, scalable and secure. National efforts to integrate and standardize data management mechanisms will aid in data dissemination and will ultimately advance research, decision-making, and public awareness of Earth observations.

-  A distinction can be made between information management and data management. Information management is the process by which data becomes useful to decision makers, and includes the mechanisms for discovering and utilizing data and metadata, optimized methods for disseminating data, and the generation and presentation of useful products. Information management facilitates the transition from content (data) to knowledge.

-  Data management infrastructure now being established by the NOAA IOOS Data Integration Framework (DIF) project, consists of:

o  Open Geospatial Consortium (OGC) Sensor Observation Service for in situ data.

o  OpenDAP/CF(Climate and Forecast) Service, OGC Web Coverage Service and NetCDF Subset Service for gridded satellite data and model output.

o  OGC Web Map Service for images of data.

o  Planned work on Registry, Catalog, discovery metadata, sensor metadata, Quality Assurance/Quality Control (QA/QC) metadata.

o  Controlled QA/QC process for both real-time and comprehensive delayed mode data.

o  Customer and client applications.

-  The respective roles of the OPeNDAP/CF Service and OGC Web Services.

-  Regional and national service agreements to promote interoperability.

-  Linking ocean observing systems into the broader Global Earth Observing System of Systems (GEOSS).

-  How we can more effectively collaborate across various national efforts to achieve globally networked information exchange.

-  Are data management and distribution problems in coastal ocean observations communities fundamentally different than the global climate oriented efforts? The coastal community lacks a unifying body like the World Meteorogical Organization (WMO) and the WMO Global Telecommunications System, yet the world’s coasts are home to most of the world’s population.

-  Integration of model predictions with Geographic Information System (GIS) information (e.g., physical observed fields to natural resources observations): challenges and needs.

-  Infrastructure needs to support observational, model prediction and analysis need for decision support from the local to global scale.

-  Observations are key both for validating model predictions and for assimilation to minimize errors in the next hindcast or predictive cycle.