HR: 0800h
AN: SF31A-0709    [Abstracts]
TI: Autonomous Underwater Vehicle Data Management and Metadata Interoperability for Coastal Ocean Studies
AU: * McCann, M P
EM: mccann@mbari.org
AF: Monterey Bay Aquarium Research Institute, 7700 Sandholdt Road, Moss Landing, CA 95039-9644 United States
AU: Ryan, J P
EM: ryjo@mbari.org
AF: Monterey Bay Aquarium Research Institute, 7700 Sandholdt Road, Moss Landing, CA 95039-9644 United States
AU: Chavez, F P
EM: chfr@mbari.org
AF: Monterey Bay Aquarium Research Institute, 7700 Sandholdt Road, Moss Landing, CA 95039-9644 United States
AU: Rienecker, E
EM: erich@mbari.org
AF: Monterey Bay Aquarium Research Institute, 7700 Sandholdt Road, Moss Landing, CA 95039-9644 United States
AB: Data from over 1000 km of Autonomous Underwater Vehicle (AUV) surveys of Monterey Bay have been collected and cataloged in an ocean observatory data management system. The Monterey Bay Aquarium Institute's AUV is equipped with a suite of instruments that include a conductivity, temperature, depth (CTD) instrument, transmissometers, a fluorometer, a nitrate sensor, and an inertial navigation system. Data are logged on the vehicle and upon completion of a survey XML descriptions of the data are submitted to the Shore Side Data System (SSDS). Instrument data are then processed on shore to apply calibrations and produce scientifically useful data products. The SSDS employs a data model that tracks data from the instrument that created it through all the consuming processes that generate derived products. SSDS employs OPeNDAP and netCDF to provide data set interoperability at the data level. The core of SSDS is the metadata that is the catalog of these data sets and their relation to all other relevant data. The metadata is managed in a relational database and governed by a Enterprise Java Bean (EJB) server application. Cross-platform Java applications have been written to manage and visualize these data. A Java Swing application - the Hierarchical Ocean Observatory Visualization and Editing System (HOOVES) - has been developed to provide visualization of data set pedigree and data set variables. Because the SSDS data model is generalized according to "Data Producers" and "Data Containers" many different types of data can be represented in SSDS allowing for interoperability at a metadata level. Comparisons of appropriate data sets, whether they are from an autonomous underwater vehicle or from a fixed mooring are easily made using SSDS. The authors will present the SSDS data model and show examples of how the model helps organize data set metadata allowing for data discovery and interoperability. With improved discovery and interoperability the system is helping us understand processes such as benthic pelagic coupling and factors that control phytoplankton productivity in coastal waters.
UR: http://www.mbari.org/ssds/
DE: 9820 Techniques applicable in three or more fields
DE: 4894 Instruments and techniques
DE: 4271 Physical and chemical properties of seawater
DE: 4299 General or miscellaneous
SC: Special Focus: Advances in Data Acquisition, Management, Analysis and Display [SF]
MN: 2004 AGU Fall Meeting