Baltic Sea
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Units: umol/l. Method: spatial interpolation produced with DIVA (Data-Interpolating Variational Analysis). URL: http://modb.oce.ulg.ac.be/DIVA. Comment: Every year of the time dimension corresponds to a 10-year centred average for each season : - winter season (December-February), - spring (March-May), - summer (June-August), - autumn (September-November). Diva settings: Snr=1.0, CL=0.7.
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Units: umol/l. Method: spatial interpolation produced with DIVA (Data-Interpolating Variational Analysis). URL: http://modb.oce.ulg.ac.be/DIVA. Comment: Every year of the time dimension corresponds to a 10-year centred average for each season : - winter season (December-February), - spring (March-May), - summer (June-August), - autumn (September-November). Diva settings: Snr=1.0, CL=0.7
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Units: umol/l. Method: spatial interpolation produced with DIVA (Data-Interpolating Variational Analysis). URL: http://modb.oce.ulg.ac.be/DIVA. Comment: Every year of the time dimension corresponds to a 10-year centred average for each season : - winter season (December-February), - spring (March-May), - summer (June-August), - autumn (September-November). Diva settings: Snr=1.0, CL=0.7
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Units: umol/l. Method: spatial interpolation produced with DIVA (Data-Interpolating Variational Analysis). URL: http://modb.oce.ulg.ac.be/DIVA. Comment: Every year of the time dimension corresponds to a 10-year centred average for each season : - winter season (December-February), - spring (March-May), - summer (June-August), - autumn (September-November). Diva settings: Snr=1.0, CL=0.7.
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Units: umol/l. Method: spatial interpolation produced with DIVA (Data-Interpolating Variational Analysis). URL: http://modb.oce.ulg.ac.be/DIVA. Comment: Every year of the time dimension corresponds to a 10-year centred average for each season : - winter season (December-February), - spring (March-May), - summer (June-August), - autumn (September-November). Diva settings: Snr=1.0, CL=0.7.
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Units: umol/l. Method: spatial interpolation produced with DIVA (Data-Interpolating Variational Analysis). URL: http://modb.oce.ulg.ac.be/DIVA. Comment: Every year of the time dimension corresponds to a 10-year centred average for each season : - winter season (December-February), - spring (March-May), - summer (June-August), - autumn (September-November). Diva settings: Snr=1.0, CL=0.7.
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EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This regional aggregated dataset contains all unrestricted EMODnet Chemistry data on contaminants (49 parameters), and covers the Baltic Sea with 3818 CDI records divided per matrices: 1358 biota (396 Vertical profiles and 962 Time series),906 water profiles, 2510 sediment profiles. Vertical profiles temporal range is from 1985-04-16 to 2016-09-27. Time series temporal range is from 1972-05-02 to 2017-10-30. Data were aggregated and quality controlled by ‘Swedish Meteorological and Hydrological Institute (SMHI)’ from Sweden. Regional datasets concerning contaminants are automatically harvested. Parameter names in these datasets are based on P01, BODC Parameter Usage Vocabulary, which is available at: http://seadatanet.maris2.nl/bandit/browse_step.php . Each measurement value has a quality flag indicator. The resulting data collections for each Sea Basin are harmonised, and the collections are quality controlled by EMODnet Chemistry Regional Leaders using ODV Software and following a common methodology for all Sea Regions. Harmonisation means that: (1) unit conversion is carried out to express contaminant concentrations with a limited set of measurement units (according to EU directives 2013/39/UE; Comm. Dec. EU 2017/848) and (2) merging of variables described by different “local names” ,but corresponding exactly to the same concepts in BODC P01 vocabulary. The harmonised dataset can be downloaded as ODV spreadsheet (TXT file), which is composed of metadata header followed by tab separated values. This worksheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ). The same dataset is offered also as XLSX file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms in subcomponents (measure, substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications users (e.g. LibreOffice Calc). The 49 parameter names in this metadata record are based on P02, SeaDataNet Parameter Discovery Vocabulary, which is available at: http://seadatanet.maris2.nl/v_bodc_vocab_v2/vocab_relations.asp?lib=P02 . Detailed documentation will be published soon. The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search
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Database of annotated data - This dataset focuses on real-time or in-situ sound signatures from marine environments. These sounds have been validated and labelled by experts (team members) and are harmonized in terms of characteristics, metadata, and format. It serves a dual purpose: as a training set to refine the AI algorithm and as a test set to validate its performance.
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During the late spring and summer of 2020, the SLU Aqua Sailor drone sails between the great Swedish islands of Öland and Gotland and collects data on the amount of fish and zooplankton. The drone survey partly takes place at the same time as the fisheries survey Sprat Acoustic Survey (Spras). Spras collects information on herring and sprat in the Baltic Sea, and is carried out with the research vessel R/V Svea. By matching data from Spras with data from the sailing drone, the researchers hope to gain better knowledge of how the Baltic Sea ecosystem works. This was repeated in 2022-2023. In 2019, SLU Aqua Sailor was used around the islands Karlsöarna in the Baltic Sea during 42 days between April and July 2019. The same survey took place In 2020 and 2021
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EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity, contaminants and marine litter. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on floating micro-litter. This dataset is the result of a validation and harmonisation process of the datasets concerning floating micro-litter present in EMODnet Chemistry. The datasets concerning micro-litter are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions. Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/ . This process was performed by ‘Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Division of Oceanography (OGS/NODC)’ from Italy. Harmonisation means that: (1) unit conversion is carried out to express variables with a limited set of measurement units and (2) merging of variables described by different “local names”, but corresponding exactly to the same concepts in BODC P01 vocabulary. The harmonised dataset can be downloaded as ODV collection that can be opened with ODV software for visualization (More information can be found at: https://www.seadatanet.org/Software/ODV ). The same dataset is offered as spreadsheet (txt format, tab separated values) where the values of the categories for the following reported parameters (type, shape, size, color, transparency and material) have been uniformed as labelled in the SeaDataNet H01, H02, H03, H04, H05, H06 vocabularies (https://vocab.seadatanet.org/search ). This format is more adapted to worksheet applications (e.g. LibreOffice Calc).