AndreaBozzo/ceres-open-data-index huggingface dataset:
EMODnet Digital Bathymetry (DTM 2020) - Tile E6

The "EMODnet Digital Bathymetry (DTM)- 2020" is a multilayer bathymetric product for Europe’s sea basins covering:
•  the Greater North Sea, including the Kattegat and stretches of water such as Fair Isle, Cromarty, Forth, Forties,Dover, Wight, and Portland 
•  the English Channel and Celtic Seas  
•  Western Mediterranean, the Ionian Sea and the Central Mediterranean Sea 
•  Iberian Coast and Bay of Biscay (Atlantic Ocean) 
•  Adriatic Sea (Mediterranean) 
•  Aegean - Levantine Sea (Mediterranean). 
•  Madeira and Azores (Macaronesia) 
•  Baltic Sea 
•  Black Sea 
•  Norwegian and Icelandic Seas 
•  Canary Islands (Macaronesia) 
•  Arctic region and Barentz Sea

The DTM is based upon more than 16360 bathymetric survey data sets and Composite DTMs that have been gathered from 49 data providers from 24 countries riparian to European seas. Also Satellite Derived Bathymetry data products have been included derived from Landsat 8 and Sentinel satellite images. Areas not covered by observations are completed by integrating GEBCO 2020 and IBCAO V4. 
The source reference layer in the portal viewing service gives metadata of the data sets used with their data providers; the metadata also acknowledges the data originators. The incorporated survey data sets itself can be discovered and requested for access through the Common Data Index (CDI) data discovery and access service that in December 2020 contained > 30.000 survey data sets from European data providers for global waters. This discovery service makes use of SeaDataNet standards and services and have been integrated in the EMODnet portal (https://emodnet.ec.europa.eu/en/bathymetry#bathymetry-services ). The Composite DTMs are described using the Sextant Catalogue Service that makes also use of SeaDataNet standards and services. Their metadata can be retrieved through interrogating the Source Reference map in the Central Map Viewing service (https://emodnet.ec.europa.eu/geoviewer/ ). 
In addition, the EMODnet Map Viewer gives users wide functionality for viewing and downloading the EMODnet digital bathymetry such as:
• water depth (refering to the Lowest Astronomical Tide Datum - LAT) in gridded form on a DTM grid of 1/16 * 1/16 arc minute of longitude and latitude (ca 115 * 115 meters).
• option to view depth parameters of individual DTM cells and references to source data
• option to download DTM in 58 tiles in different formats: ESRI ASCII, XYZ, EMODnet CSV, NetCDF (CF), GeoTiff and SD
• option to visualize the DTM in 3D in the browser without plug-in
• layer with a number of high resolution DTMs for coastal regions
• layer with wrecks from the UKHO Wrecks database.

The EMODnet DTM is also available by means of OGC web services (WMS, WFS, WCS, WMTS), which are specified at the EMODnet Bathymetry portal.  
The original datasets themselves are not distributed but described in the metadata services, giving clear information about the background survey data used for the DTM, their access restrictions, originators and distributors and facilitating requests by users to originator.
North Sea - DIVAnd 4D 6-year seasonal analysis of Water body dissolved inorganic nitrogen (DIN) 1980/2020 v2021

Moving 6-year analysis and visualization of Water body dissolved inorganic nitrogen (DIN) in the North Sea, four seasons: winter (dec-feb), spring (mar-may), summer (jun-aug), autumn (sep-nov). Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis) tool, version 2.7.2. results were subjected to the minfield option in DIVAnd to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. The depth dimension allows visualizing the gridded field at various depths.
EMODnet Digital Bathymetry (DTM 2018) - Tile A4

The "EMODnet Digital Bathymetry (DTM) - 2018" is a multilayer bathymetric product for Europe’s sea basins covering:
•  the Greater North Sea, including the Kattegat and stretches of water such as Fair Isle, Cromarty, Forth, Forties,Dover, Wight, and Portland 
•  the English Channel and Celtic Seas  
•  Western Mediterranean, the Ionian Sea and the Central Mediterranean Sea 
•  Iberian Coast and Bay of Biscay (Atlantic Ocean) 
•  Adriatic Sea (Mediterranean) 
•  Aegean - Levantine Sea (Mediterranean). 
•  Madeira and Azores (Macaronesia) 
•  Baltic Sea 
•  Black Sea 
•  Norwegian and Icelandic Seas 
•  Canary Islands (Macaronesia) 
•  Arctic region and Barentz Sea
The DTM is based upon more than 9400 bathymetric survey data sets and Composite DTMs that have been gathered from 49 data providers from 24 countries riparian to European seas. Also Satellite Derived Bathymetry data products have been included derived from Landsat 8 satellite images. The source reference layer in the portal viewing service gives metadata of the data sets used with their data providers; the metadata also acknowledges the data originators. The incorporated survey data sets itself can be discovered and requested for access through the Common Data Index (CDI) data discovery and access service that in September 2018 contained > 27.000 survey data sets from European data providers for global waters. This discovery service makes use of SeaDataNet standards and services and have been integrated in the EMODnet portal (https://emodnet.ec.europa.eu/en/bathymetry#bathymetry-services ). The Composite DTMs are described using the Sextant Catalogue Service that makes also use of SeaDataNet standards and services. Their metadata can be retrieved through interrogating the Source Reference map in the Central Map Viewing service (https://emodnet.ec.europa.eu/geoviewer/ ). 
 In addition, the EMODnet Map Viewer gives users wide functionality for viewing and downloading the EMODnet digital bathymetry such as:
• water depth (refering to the Lowest Astronomical Tide Datum - LAT) in gridded form on a DTM grid of 1/16 * 1/16 arc minute of longitude and latitude (ca 115 * 115 meters)
• option to view depth parameters of individual DTM cells and references to source data
• option to download DTM in 58 tiles in different formats: EMO, EMO (without GEBCO data), ESRI ASCII, ESRI ASCII Mean Sea Level, XYZ, NetCDF (CF), RGB GeoTiff and SD
• option to visualize the DTM in 3D in the browser without plug-in
• layer with a number of high resolution DTMs for coastal regions
• layer with wrecks from the UKHO Wrecks database.
The EMODnet DTM is also available by means of OGC web services (WMS, WFS, WCS, WMTS), which are specified at the EMODnet Bathymetry portal.  
The original datasets themselves are not distributed but described in the metadata services, giving clear information about the background survey data used for the DTM, their access restrictions, originators and distributors and facilitating requests by users to originator.
Collection of water temperature mesauring stations - ERD_EP_WATERTEMPERATURE_INSITU

EMODnet Physics collection of in situ water temperature data as recorded by platforms (Drifting Buoys, Moorings, etc.). The product offers near real time and delayed mode data. It integrates data from major marine and oceanographic initiatives and data repositories (EuroGOOS ROOS, CMS INSTAC, SeaDataNet NODCs, ICES, PANGAEA, etc.)
LifeWatch, APELAFICO Cruise 21-810: Trip 4070

Cruise 21-810 is part of the regular LifeWatch campaigns covering the Belgian Economic Exclusive Zone within the scope of the Flemish contribution to LifeWatch.eu. The dataset covers the two day cruise held from 26 to 28 October 2021 and includes all navigation, meteorological and surface hydrography parameters.The data were not calibrated against independent measures but was quality controlled for the presence of outliers, anomalous and impossible values. Data are made available at a 1minute resolution, following the international conventions agreed for this type of data.
Baltic Sea - Gulf of Riga - DIVAnd 4D seasonal analysis of Water body dissolved inorganic nitrogen (DIN) 1994/2019 v2021

Water body dissolved inorganic nitrogen (DIN) - Seasonal Climatology for Gulf of Riga for the period 1994-2019 on the domain: Lon 22.3-25.0°E, Lat 56.8-58.4°N. 
Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network.
Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7, using GEBCO 30sec topography for the spatial connectivity of water masses. Horizontal correlation length of 25 km and vertical correlation length of 10 m. Depth range: 0.0, 2.5, 5, 10, 15, 20, 25, 30, 40, 50 m. Units: µmol/l. 
The horizontal resolution of the produced DIVAnd maps grids is 0.01 degrees.
Northeast Atlantic Ocean - DIVAnd 4D seasonal 6-year average analysis of Water body dissolved inorganic nitrogen 1971/2021 v2023

Moving 6-year analysis of Water body dissolved inorganic nitrogen in the NorthEast Atlantic for each season:
 - winter: January-March,
 - spring: April-June,
 - summer: July-September,
 - autumn: October-December. 
Every year of the time dimension corresponds to the 6-year centred average of each season. 6-year periods span from 1971/1976 until 2016/2021. Observation data span from 1971 to 2021. 
Depth levels (IODE standard depths): [0.0, 5.0, 10.0, 20.0, 30.0, 40.0, 50.0, 75.0, 100.0, 125.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1750.0, 2000.0]. 
Data sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. 
Descrption of DIVAnd analysis: the computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.4, using GEBCO 30 sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps is 0.1 degrees. Horizontal correlation length varies from 400km in open sea regions to 50km at the coast. Vertical correlation length is defined as twice the vertical resolution. Signal-to-noise ratio was fixed to 1 for vertical profiles and 0.1 for time series to account for the redundancy in the time series observations. A logarithmic transformation (DIVAnd.Anam.loglin) was applied to the data prior to the analysis to avoid unrealistic negative values. Background field: a vertically-filtered profile of the seasonal data mean value (including all years) is substracted from the data. 
Detrending of data: no, advection constraint applied: no. 
Units: umol/l.
Baltic Sea - Gulf of Riga - DIVAnd 4D seasonal analysis of Water body phosphate 1994/2018 v2021

Water body phosphate - Seasonal Climatology for Gulf of Riga for the period 1994-2018 on the domain: Lon 22.3-25.0°E, Lat 56.8-58.4°N. 
Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network.
Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7, using GEBCO 30sec topography for the spatial connectivity of water masses. Horizontal correlation length of 25 km and vertical correlation length of 10 m. Depth range: 0.0, 2.5, 5, 10, 15, 20, 25, 30, 40, 50 m. Units: µmol/l. 
The horizontal resolution of the produced DIVAnd maps grids is 0.01 degrees.
Baltic Sea - DIVAnd 6-year seasonal analysis of Water body phosphate 1980/2018 v2021

Moving 6-year analysis of Water body phosphate in the Baltic Sea. Four seasons (March-May, June-August, September-November, December-February). Every year of the time dimension corresponds to a 6-year centred average. Periods span between 1980-1985 and 2013-2018. Analyses for depths (m) (HELCOM standard depths): 0, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 225, 250, 275, 300.

Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. GEBCO Grid (30 arc-seconds) topography is used for the contouring preparation. Files contain analysed fields, error fields and combined field with the deepest value for each grid point selected. Also pre-masked fields using relative error threshold 0.3 and 0.5 are included. In the analyses the Correlation length in the horizontal direction were fixed to 80 km and in the vertical direction to 25 m. Signal to noise ratio were fixed to 1.0. Background fields were created using data for the given time period and season. Log transformation was used in the analyses. No detrending, advection constraints or weighting are applied. Unit is umol/l.
LifeWatch observatory data: permanent Cetacean passive acoustic sensor network in the Belgian part of the North Sea: 2014

As part of the Belgian LifeWatch observatory, a permanent Cetacean passive acoustic network is established in the Belgian Part of the North Sea. The sensor network uses C-PODs (Chelonia Limited) to register the presence of harbour porpoise (Phocoena phocoena) in the neighbourhood. Click trains of harbour porpoises are detected and classified using the CPOD software and high and moderate quality click trains are selected. The dataset is published yearly in the highest time resolution, per minute
LifeWatch observatory data: an imaging (ZooScan) learning set from the Belgian part of the North Sea

Through regular sampling surveys, the Flanders Marine Institute (VLIZ) is generating a long-term data series for the Belgian coastal water and sandbank system, a designated site in the Long Term Ecological Research (LTER) network. This dataset contains  the learning set used to initially annotate collected images.
The data series is built from sampling activities initiated in 2012 in the framework of the LifeWatch marine observatory. Nine nearshore stations are sampled monthly, with an additional eight offshore stations sampled seasonally. The generated data series for zooplankton densities and size measurements is analysed using a ZooScan plankton imaging device together with the ZooProcess and Plankton Identifier software packages. The data are published under a CC-BY 4.0 license, allowing use of the data under the condition of providing the reference to the original source.This dataset contains the learning set.
EMODnetWCS: Access EMODnet Web Coverage Service data through R

The package was designed to make EMODnet raster data layers easily accessible in R. The package allows users to query information on and download data from all available EMODnet Web Coverage Service (WCS) endpoints directly into their R working environment. The package also allows user to specify the coordinate reference system of imported data.
EMODnetWCS depends on the R package ows4R, a general client of OGC services developed by Emmanuel Blondel
Btrait: working with biological data and trait information

<p>The R-package Btrait contains functions and data sets to work with density data, trait information and taxonomic relationships.</p><p>The package contains:</p><p>* functions to work with a combination of species-density (or species-biomass) data, species-trait information, and taxonomy</p><p>* two data sets with density and biomass data of the macrobenthos\footnote{macrobenthos are animals that live in the sediment and that are generally larger than 1 mm} in the North Sea.</p><p>* several macrobenthos trait databases</p><p>-nbsp;</p>
Phytoplankton alpha diversity in the greater Baltic Sea area

Biodiversity loss due to human activities is an increasing threat for marine ecosystems and the services we obtain from them. As biodiversity is directly related to the resilience of ecosystems to temporary disturbance, biodiversity monitoring is a vital task for areas subjected to conservation goals. Environmental factors often control the community composition and biodiversity of marine microplankton, such as the pronounced salinity gradient in the Baltic Sea (e.g. Hu et al. 2016). Time series data of biodiversity can therefore provide an indication of changes in community composition due to environmental stressors, such as climate change or eutrophication.As many biodiversity estimates are biased by sampling effort, caution must be taken when interpreting alpha diversity from microscopy phytoplankton counts. By rarefaction and evenness estimation, these biases can be reduced, but not ignored.
LifeWatch observatory data: permanent Cetacean passive acoustic sensor network in the Belgian part of the North Sea: 2017

As part of the Belgian LifeWatch observatory, a permanent Cetacean passive acoustic network is established in the Belgian Part of the North Sea. The sensor network uses C-PODs (Chelonia Limited) to register the presence of harbour porpoise (Phocoena phocoena) in the neighbourhood. Click trains of harbour porpoises are detected and classified using the CPOD software and high and moderate quality click trains are selected.

The dataset is published yearly in the highest time resolution, per minute
EMODnet Digital Bathymetry (DTM 2016) - Tile B3

The "EMODnet Digital Bathymetry (DTM) - 2016" is a multilayer bathymetric product for Europe’s sea basins covering::
• the Greater North Sea, including the Kattegat and stretches of water such as Fair Isle, Cromarty, Forth, Forties, Dover, Wight, and Portland
• the English Channel and Celtic Seas
• Western and Central Mediterranean Sea and Ionian Sea
• Bay of Biscay, Iberian coast and North-East Atlantic
• Adriatic Sea
• Aegean - Levantine Sea (Eastern Mediterranean)
• Azores - Madeira EEZ
• Canary Islands
• Baltic Sea
• Black Sea
• Norwegian – Icelandic seas

The DTM is based upon more than 7700 bathymetric survey data sets and Composite DTMs that have been gathered from 27 data providers from 18 European countries and involving 169 data originators. The gathered survey data sets can be discovered and requested for access through the Common Data Index (CDI) data discovery and access service that also contains additional European survey data sets for global waters. This discovery service makes use of SeaDataNet standards and services and have been integrated in the EMODnet portal (https://emodnet.ec.europa.eu/en/bathymetry#bathymetry-services ). The Composite DTMs are described using the Sextant Catalogue Service that makes also use of SeaDataNet standards and services. Their metadata can retrieved through interrogating the Source Reference map in the Central Map Viewing service (https://emodnet.ec.europa.eu/geoviewer/ ). 
In addition, the EMODnet Map Viewer gives users wide functionality for viewing and downloading the EMODnet digital bathymetry such as:
• water depth (refering to the Lowest Astronomical Tide Datum - LAT) in gridded form 
on a DTM grid of 1/8 * 1/8 arc minute of longitude and latitude (ca 230 * 230 meters)
• option to view depth parameters of individual DTM cells and references to source data
• option to download DTM in 16 tiles in different formats: EMO, EMO (without GEBCO data), ESRI ASCII, ESRI ASCII Mean Sea Level, XYZ, NetCDF (CF), RGB GeoTiff and SD
• layer with a number of high resolution DTMs for coastal regions
• layer with wrecks from the UKHO Wrecks database.
The NetCDF (CF) DTM files are fit for use in a special 3D Viewer software package which is based on the existing open source NASA World Wind JSK application. It has been developed in the frame of the EU FP7 Geo-Seas project (another sibling of SeaDataNet for marine geological and geophysical data) and is freely available. The 3D viewer also supports the ingestion of WMS overlay maps. The SD files can also be used for 3D viewing by means of the freely available iView4De(Fledermaus) software.

The original datasets themselves are not distributed but described in the metadata services, giving clear information about the background survey data used for the DTM, their access restrictions, originators and distributors and facilitating requests by users to originator.
Summary presence/absence maps of macro-endobenthos in European Seas, based on the EMODNET Biology database

The large databases of EMODNET Biology only store confirmed presences of taxon. However, when mapping taxon distribution, it is also important where the taxon did not occur: there is at least as much information in absences as in presences. Inferring absences from presence-only databases is difficult and always involves some guesswork. In this product we have used as much meta-information as possible to guide us in inferring absences. There is important meta-information at two different levels: the level of the data set, and the level of the taxon. Datasets can contain implicit information on absences when they have uniformly searched for the same taxon over a number of sample locations.
Normally, if the taxon would have been present there, it would have been recorded. Other datasets, however, are not informative at all about absences. Typical examples are museum collections. The fact that a specimen is found at a particular place confirms that it lived there, but does not give information on any other taxon being present or absent in the same spot. A difficulty is that some datasets have searched for a restricted part of the total community, e.g. only sampled shellfish but no worms. In this case, absence of a shellfish taxon is relevant, but absence of a worm is not. The dataset can only be used to infer absence for the taxa it has targeted. Here we implicitly assume that a dataset inventorying the endomacrobenthos, is targeting all taxa belonging to this functional group. Usually, the distinction can be made on the basis of the metadata. It is also helpful to plot the total number of taxa versus the total number of samples. Incomplete datasets have far less taxa than expected for their size, compared to 'complete' datasets. At the taxon level, taxonomic registers such as WoRMS (WoRMS Editorial Board, 2021) give information on the functional group the taxon belongs to. This information is present for many taxa, but it is most likely incomplete. The size of the register excludes any easy test of completeness of the traits. However, even if incomplete, the register trait data can be used to select the most useful datasets. If one were to use an incomplete register directly to restrict the taxa to be used in mapping, that would cause loss of interesting information. Therefore the present workflow contains additional steps using the identified promising datasets rather than the taxon list based on the register’s traits.
Temporal Turnover in European Macrobenthos Communities

This product builds on the EMODnet Biology data product Presence/absence data of macrozoobenthos in the European Seas to derive estimates of temporal turnover in benthic communities on a spatial grid across European seas. This product only uses species-level records, and only uses sampling events where the full macrobenthic community was surveyed (i.e. where there are no 'NA' values in the presence/absence dataset for any species). Six time periods are considered, based on data availability: before 1990, 1990-1999, 2000-2004, 2005-2009, 2010-2014, and 2015 and after. A 1 degree grid is used to obtain reasonable numbers of repeat samples per grid cell. The code below could be adapted to set different time periods and/or a different grid resolution. This readme describes the product structure, including the workflow to generate the required derived datasets and the process for turning them into gridded maps of community turnover.