As part of the SeaDataNet services, data sets are accessible via download services. Delivery of data to users requires common data transport formats, which interact with other SeaDataNet standards (Vocabularies, Quality Flag Scale) and SeaDataNet analysis & presentation tools (ODV, DIVA). Therefore the following data transport formats have been defined:
- SeaDataNet ODV4 ASCII for profiles, time series and trajectories,
- SeaDataNet NetCDF with CF compliance for profiles, time series and trajectories,
- SeaDataNet MedAtlas as optional extra format,
- NetCDF with CF compliance for 3D observation data such as ADCP.
Data Transport Formats manual:
Examples (ODV , Medatlas, netCDF):
The ODV4 ASCII, MedAtlas ASCII and SeaDataNet NetCDF (CF) formats have been extended with a SeaDataNet semantic header. The ODV4 format can be used directly in the popular Ocean Data View (ODV) analysis and presentation software package, which is maintained and regularly extended with new functionalities.
The SeaDataNet NetCDF (CF) format for profiles, time series and trajectories has been defined by bringing together a community comprising NetCDF and CF experts (such as from NCAR and UNIDATA), and as many users of CF NetCF for oceanographic point data as possible. This included participants from MyOcean, IMOS, Australian Navy and USNODC.
The SeaDataNet NetCDF (CF) format is based upon Version 1.6 of the CF Metadata Conventions, published by the CF community in December 2011. This publication includes a chapter on 'Discrete Sampling Geometries' to cover storage of point data in NetCDF. This was taken as starting point to formulate how basic point data - profiles, time series and trajectories - can be encoded in CF-compliant NetCDF together with the usage metadata - including parameter semantics - that SeaDataNet had included in its ASCII 'ODV format'.
The SeaDataNet NetCDF (CF) format for profiles, time series and trajectories can be used next to the SeaDataNet ODV 4 ASCII format in the services of the SeaDataNet infrastructure.
Additional feature types have been defined for the storage of multiple trajectories data like moored ADCP (Feature type = timeseriesProfile) or shipborn ADCP (Feature type = trajectory profile).