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Reiner Schlitzer Alfred Wegener Institute for Polar and Marine Research Ocean Data View Achievements and Future Developments.

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Presentation on theme: "Reiner Schlitzer Alfred Wegener Institute for Polar and Marine Research Ocean Data View Achievements and Future Developments."— Presentation transcript:

1 Reiner Schlitzer Alfred Wegener Institute for Polar and Marine Research Ocean Data View Achievements and Future Developments

2 File Aggregation File Aggregation Parameter Aggregation Parameter Aggregation

3 SDN Import Extensions Metadata enrichment (imports all CDI fields provided via csv files) Imports instrument code and fall-rate information from data files Supports SDN netCDF files in addition to SDN/ODV txt files New 64-bit ODV allows import of all SDN data files in one go

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6 P35 Parameter Aggregation Source ODV collection must have been produced via option Import > SDN Formats option Import > SDN Formats using ODV 4.6.3 or later using ODV 4.6.3 or later Automatically downloads up-to-date versions of P35 vocab and conversion database

7 Unit Conversion Database

8 P35 aggregated variables Other source variables not in any P35 variable

9 P35 Aggregation Rules P35 aggregated variables use SDN quality flags If a given file only contains data for one contributing variable (e.g., DOXYZZ01): data value and quality flag are used as given (covers >95% of cases) If a given file contains data for more than one contributing variable: median of contributing data values is used quality flag inheritence (poorest quality contributor rule)

10 ODV API First released Sep 2013 Used by IFREMER OCEANOTRON to serve data in ODV collections over the Internet Version 2 released March, 26 2015 Supports concurrent use of a collection; added usage safeguards; 64bit support

11 Per-Station Data History History information stays with station data when exporting to ODV spreadsheet or ODV collection.

12 Data Errors, Quality Flags and Data Infos

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14 Future Development: WebODV Objective: provide ODV services over the Internet (data search, download, QC, and visualization) using centrally administered community datsets on a server such as the EMODnet / SeaDataNet aggregated datasets Poster at IMDIS 2016


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