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Ocean Data View and its Role in SeaDatanet. Reiner Schlitzer Alfred Wegener Institute for Polar and Marine Research. Ocean Data View. Software for easy access, interactive analysis and visualization of profile or sequence data. Available for Windows , Mac OS X, Linux, and UNIX .
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Ocean Data View and itsRole in SeaDatanet Reiner Schlitzer Alfred Wegener Institute for Polar and Marine Research
Ocean Data View Software for easy access, interactive analysis and visualization of profile or sequence data. • Available for Windows, Mac OS X, Linux, and UNIX. • Freely available for research and teaching. • Supports native ODV collection format and netCDF. • Maintains data quality flags. • Reads and imports all major oceanographic data formats including: • World Ocean Database (WOD) format, • various WOCE formats and data types, • ARGO profile and trajectory formats, • SD2 format, • various spreadsheet formats. http://odv.awi.de
Station Selection Build large data collections Analyze station subset Apply selection criteria
ODV Data Format • optimized for variable length profiles/sequences (original data or data products) • binary format providing dense storage and fast data access • support for data quality flags • expandable • platform-independent • can be used for many different data types Many important oceanographic and other geo-referenced datasets are available for download as ready-to-use ODV collections…
South Atlantic Ventilation Experiment (SAVE) Oceanography – Historical Data Reid & Mantyla
Other – River Discharge Vorosmarty, Fekete, and Tucker (1018 stations)
ODV’s Role in SeaDatanet Integrate ODV into the SeaDatanet framework and use it as a common data manipulation and visualization tool. 1. Provide access to SeaDatanet datastreams for scientific use. [uses common exchange formats (JRA1), provides linkage between data centers and scientific community, possible once SeaDatanet datasets are available] 2. Use ODV for quality control within SeaDatanet data centers. [usesSeaDatanet QC procedures and flagging schemes (JRA1), requires automatic tools for export from and re-import into native databases, should be implemented early on] 3. Use ODV for capacity building and training [conduct training courses (NA3) and teach basic data handling and quality assurance procedures]
Data Editing and Quality Control • easy spotting and identification of outliers or offsets • painless editing of data value and quality flag • logging of all value or flag modifications • automatic range checks and manual or automatic editing
ODV Integration into Data Center Operations Core Database