AndreaBozzo/ceres-open-data-index huggingface dataset:
EMODnet Human Activities, Desalination, Plants

The database on Desalination plants in the EU was created in 2021 by Cogea Srl for the European Marine Observation and Data Network (EMODnet). It is the result of the harmonization of a dataset provided by GWI DesalData. The dataset provides spatial information (point) on the centroid of the municipality where a given plant is located. It is available for viewing and download on EMODnet - Human Activities web portal (https://emodnet.ec.europa.eu/en/human-activities) and will be updated every year. The dataset covers the following countries: Albania, Austria, Belgium, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Finland, France, Georgia, Germany, Gibraltar, Greece, Guernsey, Hungary, Ireland, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Netherlands, Norway, Poland, Portugal, Romania, Russia, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, Ukraine. Where available, each point has the following attributes: site code (ID), Location Name, Country, Position Source, Commune Name, NUTS code (NUTS 3 ID), Latitude, Longitude. A relational table provides further information for each desalination plant where data are available: Location Type, Project, Capacity (m3/d), Size, Units, Unit Size (m3/d), Technology, Feedwater, Plant Type, Award Date, Online Date, Plant Status, Customer Type, Industry Type, Customer, Holding Company, Plant Owner. More plant-specific information is available in the original dataset.
Contaminants-Cadmium: water stations v2019

This product displays the stations present in EMODnet validated dataset where cadmium levels have been measured in water.
EMODnet Chemistry has included the gathering of contaminants data since the beginning of the project in 2009. 
For the maps for EMODnet Chemistry Phase III, it was requested to plot data per matrix (water,sediment, biota), per biological entity and per chemical substance. 
The series of relevant map products have been developed according to the criteria D8C1 of the MSFD Directive, specifically focusing on the requirements under the new Commission Decision 2017/848 (17th May 2017). The Commission Decision points to relevant threshold values that are specified in the WFD, as well as relating how these contaminants should be expressed (units and matrix etc.) through the related Directives i.e. Priority substances for Water. EU EQS Directive does not fix any threshold values in sediments. On the contrary Regional Sea Conventions provide some of them, and these values have been taken into account for the development of the visualization products.
To produce the maps the following process has been followed:
    1. Data collection through SeaDataNet standards (CDI+ODV)
    2. Harvesting, harmonization, validation and P01 code decomposition of data
    3. SQL query on data sets from point 2 
    4. Production of map with each point representing at least one record that match the criteria
The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols.
Preliminary processing were necessary to harmonize all the data :
    • For water: contaminants in the dissolved phase;
    • For sediment: data on total sediment (regardless of size class) or size class < 2000 μm
    • For biota: contaminant data will focus on molluscs, on fish (only in the muscle), and on crustaceans
    • Exclusion of data values equal to 0
Ecoscope Balbaya Database

Base de données fines corrigées (pour la composition spécifique ; les données sont obtenues à partir de la base de données AVDTH à laquelle on a appliqué le traitement nommé T3) sur les données thonières à l'échelle de la mareé (calée par calée, espèce par espèce). Données nationales de captures, efforts et tailles de la pêche au thon tropical de surface. Contient des données OA et OI entre 2001 et 2006 uniquement sur les captures et efforts (à vérifier ?). Pas d'échantillons ? A VERIFIER. La liste des espèces identifées dans cette base de données a été prise en compte dans la base Ecoscope.
Balbaya est une base de données fines qui contient l'ensemble des données de captures, efforts et mensurations de la pêche thonière tropicale de surface (canneurs, senneurs) française à l'échelle du navire (calée par calée, espèce par espèce, pas d'activités autres que les calées). Les données sont obtenues à partir de la base AVDTH à laquelle est appliqué le traitement T3 qui permet de corriger la composition spécifique des captures et d'homogénéiser les tailles échantillonnées (poissons mesurés en longueur dorsale et extrapolation des tailles aux poissons comptés. Balbaya contient des données pour l'océan atlantique et l'océan indien de 1991 à 2010. Contrairement à AVDTH, Balbaya est une base unique qui contient à la fois les données océan indien et océan atlantique. Elle a été créée pour centraliser l'ensemble des jeux de données disponibles corrigés, et rendre plus facilement accessibles les données disponibles dans les fichiers m11 et nn.t issus de T3. Cette base est hébergée (i) sur un serveur (aldabra2) du CRH (UMR EME 212), (ii) sur un serveur du centre IRD de Montpellier, et est accessible à toute personne disposant d'un identifiant et d'un mode de passe d'accès délivré, après examen de la demande, par le responsible de l'Observatoire Thonier. Notons que l'Instituto Espanol de Oceanografia (IEO) dispose également d'une base Balbaya (identique en terme de structure) et à jour jusqu'en 2010 pour les données espagnoles ; une analyse collaborative (IRD-IEO) des deux bases est en cours avec pour objectif la construction d'une base commune résultant de la fusion des deux précédentes (i.e. données des senneurs européens et des navires seychellois, qui sont en fait espagnols).
Balbaya est utilisée au sein de différents organismes : CRH (Centre de Recherches Halieutiques Méditerranéennes et Tropicales, Sète (France) et IEO (Instituto Espanol de Oceanografia, Espagne).

Les données présentées ici proviennent d'une extraction des données pour lesquelles la position géographique et la date de l'observation fournies sont certaines. D'autres observations existent avec une résolution spatio-temporelle moins fine (plus d'incertitude sur la position et la date des captures).
Size Indian Nematodes

Length and width measurements of 800 nematodes from the Indian Ocean. Four stations were sampled, each with two replicates. The sampling depths varied from 50 to 2000 meters. The density (ind/m²) and the SCOC (mmol O2/m²/day) were calculated.
The aim of collecting these data was to investigate the effect of oxygen, granulometry and food availability on the nematode density and community structure along four parallel bathymetric transects off the Kenyan coast.
Brachiopoda distribution data from: Deep-sea fauna of European seas - an annotated species check-list of benthic invertebrates living deeper than 2000 m in the seas bordering Europe

An annotated check-list is given of Brachiopoda species occurring deeper than 2000 m in the seas bordering Europe.
The check-list is based on published data. The check-list includes 12 species. For each species synonymy, data on localities in European seas and general species distribution are provided. Station data are presented separately in the present thematic issue.
540_DTM_1-128_S201504900-1

The DTM is produced from the S201504900-1 multibeam echosounder survey, acquired in 2015. The resolution is 1/128 arc-minutes (~15m).  It is located close to Ouessant (France) with depths from -44.2m to -100.2m. Depths are referenced to the Lowest Astronomical Tide and the coordinates are expressed into the WGS84 reference frame. Data and metadata associated to the survey are available on the website http://diffusion.shom.fr/pro/lots-bathy.html. The DTM is not to be used for navigation.
EMODnet Human Activities, Aquaculture, Shellfish

The dataset on shellfish aquaculture in the Eropean seas was created in 2014 by AND-International for the European Marine Observation and Data Network (EMODnet). It is the result of the aggregation and harmonization of datasets provided by national sources across the EU (plus Norway and the UK) and by the project Euroshell. The dataset contains points representing shellfish farms or shellfish production areas (depending on available data) in the following countries: Bulgaria, Denmark, France, Greece, Ireland, Italy, Netherlands, Norway, Slovenia and United Kingdom. Data from Bulgaria, Denmark, Greece, Ireland, Norway and Scotland come from the official lists of registered aquaculture sites. Data from France relies on cadastral data. Data from the Netherlands, Italy and England and Wales come from the Euroshell project. Data is missing for Spain, Germany, Portugal, Sweden and Croatia. Except for Spain and Germany, the shellfish production remains limited in those MS. There is no production in other MS. Each point has the following attributes (where available): status (active, inactive, licensed), country, owner name, farm type (Mussels, Oysters, Mussels-Oysters, Clams, Specialised (other), Mixed (other)), production method (Beds, Long lines,  Rafts,    Saltwater closed (recirculation),   Saltwater ponds, Saltwater tanks/raceways, Trestles or trays, Other), production stage (Grow out for human consumption, Hatchery, Nursery, Broodstock, Reproduction,  Harvest, Other), purpose (Commercial, Research, Education, Display, Other), products detailed (English translation of the information provided on species grown or authorised in the source), point information (Polygon centroid, Original) depending on how the information is provided in the source (polygons or points), site_id,  distance to coast (metres), position from coastline (At sea, within the coastline).  The farm type relies on a typology established by AND-International, based on available information on species grown or authorised. A relational table provides harmonised information about species grown or authorised using Eurostat nomenclature for the Species Group (Mussels; Oysters;  Clams, cockles, arkshells;  Scallops, pectens;  Abalones, winkles, conchs;  Sea-urchins and other echinoderms) and when available the species name (e.g. Blue mussels - Mytilus edulis). The distance to coast (EEA coastline shapefile) has been calculated using the original data map projections, where available. In the other cases it was used the UTM WGS84 Zone projected coordinate system where data fall in. Compared with the previous version this new version includes updated data for Denmark, Greece, Ireland, Norway and Scotland and new data from Slovenia. Data are available for viewing and download on EMODnet - Human Activities web portal (https://emodnet.ec.europa.eu/en/human-activities).
Probability maps for different phytoplankton species in the North Sea

This data product is a series of probability of occurrence maps for 200 phytoplankton species from 1995 to 2015 in the Greater North Sea, based on a neural network analysis. The input data files have been produced by Deltares (Luuk van der Heijden, Willem Stolte). They used EMODnet-Biology data as a basis. The selection of relevant datasets was optimized in order to find all planktonic species, and exclude all species that are not planktonic. The occurences from EMODnet Biology were complemented with absence data assuming fixed species lists within each dataset and year.

In addition to the occurrence data, the environmental variables bathymetry, silicate, phosphate and nitrate concentrations were used. Additionally the position (latitude and longitude) and the year are provided to the neural network. DIVAnd (n-dimensional Data-Interpolating Variational Analysis) and the neural network library Knet were used in this analysis.
2015_9_SNH South Arran And Upper Loch Fyne Marine Protected Areas: T3 1/128

This survey area was part of a multibeam bathymetry carried out by the British Geological Survey on behalf of Scottish Natural Heritage between 25/11/2015  and 17/04/2016. A bathymetric and side scan sonar survey was undertaken using the survey vessel White Ribbon. The aim was to establish baseline mapping of the seabed (examining habitat heterogeneity and fisheries marks) within the target areas prior to the implementation of new management measures.
Seasonal variation of the zooplankton community at Gazi, Lamu and Malindi (Kenya) sampled between 1990 and 1992

Copepoda species list, zooplankton densities and measurement of environmental variables at Gazi, Malindi and Lamu sampled between March and December 1992. The data were digitized by VLIZ from the original report: Osore, M. K. W. (1994). A study of the zooplankton of Gazi Bay, Kenya and the adjecent waters: community structure and seasonal variation. MSc Thesis. Universiteit Gent: Ghent. 112 pp.
Zooplankton was sampled using a Bongo net at three stations in Gazi Bay between March 1990 and February 1992. A total of 114 samples were collected alongside environmental variables of temperature, salinity, dissolved oxygen, pH and transparency. Additional samples were collected on three transects off the Kenyan coast between 19th November and 5th December 1992.
EMODnet Bathymetry - Bathymetric Contours version 2022

The EMODnet Bathymetric Contours are available as a WFS service from EMODnet Bathymetry. Service URL is: https://ows.emodnet-bathymetry.eu/wfs

The bathymetric contours of this layer are generated automatically based on the EMODnet DTM. New contour sets will be available for each consecutive update of the EMODnet DTM. The contours are generated by GGSgc BV using the proprietary GGSgc software.
269_DTM_KorinthiakosGulf

The DTM is a compilation of multibeam echosounder surveys at Korinthiakos Gulf (Greece) acquired with R/V Aegaeo using Seabeam 2120 (20 kHz) echosounder from 2001 to 2004. Grid resolution is 1/32 arc-minutes  processed for the purpose of the HR DTMs layer of EMODnet Bathymetry HRSM, October 2018.
2011/2: Firth of Lorn North: Area 2: 1/128

This British Geological Survey (BGS) marine multibeam and sampling survey took place over two separate periods (15-18 February and 24 February - 5 March 2011) in an area at the northern tip of the Firth of Lorne, Oban Bay on board the Northern Lighthouse Board vessel NLV Pole Star. Sea floor data were collected using an EM3002D multibeam system.
Contaminants-Hexachlorobenzene: water stations v2019

This product displays the stations present in EMODnet validated dataset where hexachlorobenzene levels have been measured in water.
EMODnet Chemistry has included the gathering of contaminants data since the beginning of the project in 2009. 
For the maps for EMODnet Chemistry Phase III, it was requested to plot data per matrix (water,sediment, biota), per biological entity and per chemical substance. 
The series of relevant map products have been developed according to the criteria D8C1 of the MSFD Directive, specifically focusing on the requirements under the new Commission Decision 2017/848 (17th May 2017). The Commission Decision points to relevant threshold values that are specified in the WFD, as well as relating how these contaminants should be expressed (units and matrix etc.) through the related Directives i.e. Priority substances for Water. EU EQS Directive does not fix any threshold values in sediments. On the contrary Regional Sea Conventions provide some of them, and these values have been taken into account for the development of the visualization products.
To produce the maps the following process has been followed:
    1. Data collection through SeaDataNet standards (CDI+ODV)
    2. Harvesting, harmonization, validation and P01 code decomposition of data
    3. SQL query on data sets from point 2 
    4. Production of map with each point representing at least one record that match the criteria
The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols.
Preliminary processing were necessary to harmonize all the data :
    • For water: contaminants in the dissolved phase;
    • For sediment: data on total sediment (regardless of size class) or size class < 2000 μm
    • For biota: contaminant data will focus on molluscs, on fish (only in the muscle), and on crustaceans
    • Exclusion of data values equal to 0
Baltic Sea DIVA 4D analysis of Water_body_nitrate

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
Seafloor litter - Fishing related items density normalized per km² 2011/2024 v2025

This visualization product displays fishing related items density per trawl.

EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). 
The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during bottom trawl surveys.

In cases where the wingspread and/or the number of items were/was unknown, it was not possible to use the data because these fields are needed to calculate the density. Data collected before 2011 are concerned by this filter.

When the distance reported in the data was null, it was calculated from:
- the ground speed and the haul duration using the following formula: Distance (km) = Haul duration (h) * Ground speed (km/h);
- the trawl coordinates if the ground speed and the haul duration were not filled in.

The swept area was calculated from the wingspread (which depends on the fishing gear type) and the distance trawled:
Swept area (km²) = Distance (km) * Wingspread (km)

Densities were calculated on each trawl using the following computation:
Density of fishing related items (number of items per km²) = ∑Number of fishing related items / Swept area (km²)

Percentiles 50, 75, 95 & 99 were calculated taking into account data for all years.

The list of selected items for this product is attached to this metadata.
Information on data processing and calculation is detailed in the attached methodology document.

Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the Marine Litter Database for this area.
EMODnet Digital Bathymetry (DTM 2024) - Tile B5

The "EMODnet Digital Bathymetry (DTM)- 2024" 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 22032 bathymetric survey data sets and Composite DTMs that have been gathered from 66 data providers from 28 countries riparian to European seas and beyond. Also Satellite Derived Bathymetry data products have been included fro Landsat 8 and Sentinel satellite images. Areas not covered by observations are completed by integrating GEBCO 2024 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 contains > 41.000survey data sets from European data providers for global waters. The Composite DTMs can be discovered through the Sextant Catalogue service. Both discovery services make use of SeaDataNet standards and services and have been integrated in the EMODnet portal (https://emodnet.ec.europa.eu/en/bathymetry#bathymetry-services ).
In addition, the EMODnet Map Viewer (https://emodnet.ec.europa.eu/geoviewer/ ) 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 59 tiles in different formats: ESRI ASCII, XYZ, EMODnet CSV, NetCDF, 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.
PANGAEA - Data from Long-term Ecological Research @ AWI (LTER)

This dataset contains data from the Long Term Ecological Research (LTER) Project at AWI. These data are derived from PANGAEA.
This dataset contains data from the Long Term Ecological Research (LTER) Project at AWI. These data are derived from PANGAEA.

Rationale of the LTER Project:

"The future has already arrived; it just isn't evenly distributed" (W. Gibson)

This is exactly our problem with the response of ecosystems to long-term trends in climate and environment. Owing to ecosystem complexity and variability in space and time, the phenomena we deal with are either long term in their dynamics, or episodic, rare, complex or subtle in their occurrence and/or manifestation. Only long-term studies, combined with experimental approaches, can reveal ecosystem dynamics, patterns and control processes. Hence, long-term research is essential to make and justify management and policy decisions regarding the protection of ecosystems and the maintenance of ecosystem services, particularly in times of potentially rapid climate change.

Objectives of the LTER Project:

To continue/establish time series of relevant and representative ecological parameters at different levels of ecosystem organisation.To create well documented databases and archives of samples and specimens that are accessible to the scientific community.To analyze these time series for trends and cycles by means of modern analytical  and modelling approaches.To relate the observed patterns to external forcing factors on regional and global scales by means of empirical and mechanistic models.To establish a cause-and-effect understanding of these relationships by analytical and experimental approaches.To model future ecological developments based on the observed relationships between forcing factors and ecological parameters.To provide knowledge to the broader scientific community, general public, resource managers, and policy makers to address complex environmental challenges.

AWI LTER Activities:

Two ecological research series maintained by AWI go back to the 1960s:the Helgoland Roads plankton time series (one station, daily since 1962),the German Bight soft bottom zoobenthos time series (two stations, bi-annual, since 1969)
During the 1980s/90s further long-term research series on plankton, bottom fauna and flora and fish have been established that focus on the German Bight and the North Frisian Wadden Sea.