AndreaBozzo/ceres-open-data-index huggingface dataset:
Gridded abundance maps of marine birds around the Azores

Gridded abundance map of marine birds around the Azores. This product was developed with DIVA (Data-Interpolating Variational Analysis). Data was provided by the Azores Fisheries Observation Programme (POPA).
This dataset is based on:
Machete, M.; Institute of Marine Research (IMAR), Portugal; Department of Oceanography and Fisheries, University of the Azores (DOP/UAC), Portugal; (2014): POPA- Fisheries Observer Program of the Azores: Seabird sightings in the Azores tuna fishery from 1998 to 2013: during the capture of live bait. http://dx.doi.org/10.14284/10
Machete, M.; Institute of Marine Research (IMAR), Portugal; Department of Oceanography and Fisheries, University of the Azores (DOP/UAC), Portugal; (2014): POPA- Fisheries Observer Program of the Azores: Seabird sightings in the Azores tuna fishery from 1998 to 2013: while fishing. http://dx.doi.org/10.14284/12
Machete, M.; Institute of Marine Research (IMAR), Portugal; Department of Oceanography and Fisheries, University of the Azores (DOP/UAC), Portugal; (2016): POPA- Fisheries Observer Program of the Azores: Seabird sightings in the Azores tuna fishery from 2000 on: during navigation or search mode. http://dx.doi.org/10.14284/11
Micro litter - Size of litter per net - Other specific protocols 2011/2021 v2025

This visualization product displays the size of litter in percent per net per year from specific protocols different from research and monitoring protocols.
EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10).
A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter.
European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization.

A filter is applied to represent only micro-litter sampled according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye.

To calculate percentages for each size, formula applied is:
Size (%) = (∑number of particles of each size)*100 / (∑number of particles of all size)
When the number of micro-litters was not filled or was equal to zero, it was not possible to calculate the percentage.

Standard vocabularies for micro-litter size classes are taken from Seadatanet's H03 library (https://vocab.seadatanet.org/v_bodc_vocab_v2/search.asp?lib=H03 ). Different protocols with different degrees of precision were used to classify the sampled micro-litters. Consequently, on the map, the distribution of micro-litter in the size classes depends on the protocol applied during the survey.

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 National Oceanographic Data Centre (NODC) for this area.
Important Marine Mammal Areas (IMMA)

The IUCN MMPATF IMMA is a joint project between the IUCN Species Survival Commission (SSC) and World Commission on Protected Areas (WCPA).IMMA layer indicates discrete portions of habitat, important to marine mammal species that have the potential to be delineated and managed for conservation.IMMAs are not marine protected areas (MPAs). IMMAs are identified based on scientific expert knowledge, along with peer review, in order to prioritise their consideration for conservation measures by governments, intergovernmental organisations, conservation groups, industry or business, and the general public.
The IMMA spatial layer aims to attract the attention of policy- and decision-makers to the opportunity, as well as to the need, to ensure the favourable conservation status of marine mammals in specific areas through the implementation of the most appropriate management measures. This can include an MPA designation, shipping or fishing regulations, and/or monitoring. However, IMMAs per se are a scientific knowledge product totally devoid of management implications.Dedicated efforts to identify IMMAs have not yet covered all of the global ocean but global coverage is anticipated in the near future.Waters outside of IMMAs in all areas of the ocean may still be important for the long-term survival and well-being of marine mammals.Human activities taking place in marine environments everywhere must be conducted responsibly.Information described include the name, location, marine mammal species of importance, the broad level and finer sub-divisions criteria used, and the area size of the IMMA.The IUCN IMMA layer has been created to be compatible with and inform the identification of other area-based management tools and conservation prioritisation areas and include but are not restricted to Ecologically or Biologically Significant Area (EBSA), Key Biodiversity Area (KBA), Important Bird and Biodiversity Area (IBA), RAMSAR Convention Site (RAMSAR), Cetacean Critical Habitat (CCH), Biologically Important Area (BIA) and Important Shark and Ray Area (ISRA).For more information about IMMAs and to download the layers and obtain information on species and criteria, please go to the IMMA website: www.marinemammalhabitat.org
Waterbase - Transitional, coastal and marine waters

Waterbase is the generic name given to the EEA databases on the status and quality of Europes rivers, lakes, groundwater bodies and transitional, coastal and marine waters, and on the quantity of Europes water resources
Waterbase is the generic name given to the EEA databases on the status and quality of Europes rivers, lakes, groundwater bodies and transitional, coastal and marine waters, and on the quantity of Europes water resources.

Waterbase contains a series of web pages through which the user can access nationally validated, aggregated data and information on the status and quality of Europe’s water environment. Although many countries make their monitoring data available over the Internet (e.g. in state-of-the-environment reports), the level and form of accumulation and combination of data often varies from country to country which makes detailed quantitative comparisons difficult. Waterbase data collected through the Eurowaternet network are comparable at the European level.
Waterbase data are primarily used in the production of the EEA's indicator fact sheets, which are the basis of European assessments.
North East Atlantic Ocean - Eutrophication and Acidity aggregated datasets 1921/2017 v2018

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). ITS-90 water temperature and Water body salinity variables have been also included (as-is) to complete the Eutrophication and Acidity data. If you use these variables for calculations, please refer to SeaDataNet for having the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets . This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (16 parameters with quality flag indicators), and covers the Northeast Atlantic Ocean (40W) with 106885 CDI records (106339 Vertical profiles and 546 Time series). Vertical profiles temporal range is from 1921-10-15 to 2017-09-30. Time series temporal range is from 1974-06-14 to 2017-08-01. Data were aggregated and quality controlled by 'IFREMER / IDM / SISMER - Scientific Information Systems for the SEA' from France.
Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium.
Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/.
Detailed documentation is available at: https://doi.org/10.6092/ec8207ef-ed81-4ee5-bf48-e26ff16bf02e
The aggregated dataset can be downloaded as ODV spreadsheet, 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 original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search
Mollusk death assemblages collected from Cuba in the Gulf of Guanahacabibes (2014) and the Gulf of Batabanó (2015)

Data collected during two expeditions in the western part of Cuban Archipelago: one in the Gulf of Guanahacabibes (GG) (Southeastern Gulf of Mexico), and the other in the Gulf of Batabanó (GB) (Northwestern Caribbean Sea). In GG were included seven sites that were sampled between May 30th–June 10th in 2014. In GB were included four sites that were sampled from May 1st–5th in 2015. All samples were collected from soft-bottom sites, either from coral reefs sandy spots or seagrass meadows.
Sediment samples were collected by SCUBA diving using a box core (= sampling unit) with an effective sampling area of 100 cm2. The box core was pushed 10 cm into the bottom collecting approximately 1000 cm3 of sediments. Generally, three sample units were collected per site. Sediments were sieved through a 500-μm sieve and preserved in 70% ethanol. All mollusk shells were sorted and counted, in the case of the bivalves, each disarticulated valve was counted as an individual. This dataset includes the complete shells and the large skeletal fragments retaining the apex or more than half of the hinge line.
Mediterranean Sea DIVA 4D analysis of Water_body_nitrite

Moving 10-years analysis of nitrite at Mediterranean Sea for each season :
- winter (January-March),
- spring (April-June),
- summer (July-September),
- autumn (October-December).

Every year of the time dimension corresponds to the 10-year centered average of each season.
Decades span from 1965-1974 until 2004-2013.
Observational data span from 1961 to 2013.
Depth range (IODE standard depths): -1500.0, -1400.0, -1300.0, -1200.0, -1100.0, -1000.0, -900.0, -800.0, -700.0, -600.0, -500.0, -400.0, -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0, -30.0, -20.0, -10.0, -5.0, -0.0.

Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network.

Description of DIVA analysis:  Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. Profiles were interpolated at standard depths using weighted parabolic interpolation algorithm (Reiniger and Ross, 1968). GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5.

DIVA settings: A constant value for signal-to-noise ratio was used equal to 3. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used.

Logarithmic transformation applied to the data prior to the analysis.
Background field: the data mean value is subtracted from the data.
Detrending of data: no.
Advection constraint applied: no.

Originators of Italian data sets-List of contributors:
o	Brunetti Fabio (OGS)
o	Cardin Vanessa, Bensi Manuel doi:10.6092/36728450-4296-4e6a-967d-d5b6da55f306
o	Cardin Vanessa, Bensi Manuel, Ursella Laura, Siena Giuseppe doi:10.6092/f8e6d18e-f877-4aa5-a983-a03b06ccb987
o	Cataletto Bruno (OGS)
o	Cinzia Comici Cinzia (OGS)
o	Civitarese Giuseppe (OGS)
o	DeVittor Cinzia (OGS)
o	Giani Michele (OGS)
o	Kovacevic Vedrana (OGS)
o	Mosetti Renzo (OGS)
o	Solidoro C.,Beran A.,Cataletto B.,Celussi M.,Cibic T.,Comici C.,Del Negro P.,De Vittor C.,Minocci M.,Monti M.,Fabbro C.,Falconi C.,Franzo A.,Libralato S.,Lipizer M.,Negussanti J.S.,Russel H.,Valli G., doi:10.6092/e5518899-b914-43b0-8139-023718aa63f5
o	Celio Massimo (ARPA FVG)
o	Malaguti Antonella (ENEA)
o	Fonda Umani Serena (UNITS)
o	Bignami Francesco (ISAC/CNR)
o	Boldrini Alfredo (ISMAR/CNR)
o	Marini Mauro (ISMAR/CNR)
o	Miserocchi Stefano (ISMAR/CNR)
o	Zaccone Renata (IAMC/CNR)
o	Lavezza, R., Dubroca, L. F. C., Ludicone, D., Kress, N., Herut, B., Civitarese, G., Cruzado, A., Lefèvre, D., Souvermezoglou, E., Yilmaz, A., Tugrul, S., and Ribera d'Alcala, M.: Compilation of quality controlled nutrient profiles from the Mediterranean Sea, doi:10.1594/PANGAEA.771907, 2011.
2012/9_MS: Argyll Array: South-west of Tiree: Cable North: 1/128

This marine geophysical and multibeam survey was undertaken by British Geological Survey on behalf of Marine Scotland utilising the Northern Lighthouse Board vessel NLV Polestar, it took place in July/August 2012 off south-west Tiree. The purpose was to further our understanding of Scotland’s marine environment, increase the efficiency of use of public resources, enhance the safety of those at sea and contribute to new policy priorities such as marine protected areas, wider conservation measures, marine planning and renewable. Bathymetric data was collected using a Kongsberg EM3002D dual head, multibeam system. Data was acquired using a Kongsberg SIS operating system, logging raw .ALL files. This data was processed offline by BGS using CARIS HIPS and SIPS 7.1 SP2.
Romanian Black Sea Phytoplankton data from 1975 to 1980

The phytoplankton dataset includes samples collected from shallow to shelf Romanian waters, in the period 1975 - 1980, from March to November; there is no similar frequency each year. Dataset contains abundance data (cells per liter) and biomass (mg/m3) for individual phytoplankton taxa.
Phytoplankton data collected in the Black Sea between 1975 and 1980 and processed by Nicolae Bodeanu, Anca Roban and Mioara Usurelu. This dataset contains abundance data (cells per liter) and biomass (mg/m3) for individual phytoplankton taxa. Samples were taken by 1L Nansen bottle at standard depths. The standard sedimentation technique for samples preparation (Morozova-Vodianitkaia, 1954) was used. Data were collected from coastal/shallow to shelf Romanian waters from various transects such as: Sulina, Mila and Sf. Gheorghe (northern zone) to Constanta, Tuzla, Mangalia (southern zone).  
Phytoplankton abundance was counted by specialists using data sheets which contained abundance per station. After counting all the individuals from a subsample under the microscope, the scientific team calculated the total phytoplankton abundance and biomass. For each record, the maximum and minimum sampling depth is recorded.
Arctic Ocean - DIVAnd 4D 6-year seasonal analysis of Water body dissolved oxygen concentration 1965/2022 v2023

Moving 6-year analysis of dissolved oxygen concentration in the Arctic Ocean, for each season in the period 1965-2022. Every year of the time dimension corresponds to the 6-year centered average for each season. Winter: December-February, Spring: March-May, Summer: June-August, Autumn: September-November. Depth range (IODE standard depths): 0, 5, 10, 20, 30, 40, 50, 75, 100, 125, 150, 200, 250, 300, 400, ..., 1500, 1750, 2000, 2500m. Units: umol/l. Description of DIVA analysis: The computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.9, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is 0.1 degrees.  Signal-to-noise ratio was fixed to 3.0, horizontal correlation length varying from 45 km near the coast to 150 km, and vertical correlation length varying between 25 and 1000 m. Logarithmic transformation is applied to the data prior to the analysis. Background field: analysis with signal-to-noise ratio = 10, horizontal correlation length 60-200 km, and vertical correlation length 25-1000 m.
EMODnet Human Activities, Aquaculture, Marine Finfish

The Marine Finfish Aquaculture Dataset provides the locations of marine finfish farms in the EU and partner countries. Data were collected through several sources, including data published by Member States in compliance with the EU Animal Health Law, publicly available databases for certain countries (e.g. Norway, Denmark, and Scotland), and data obtained upon request from some national authorities. The dataset shows data from Croatia, Cyprus, Denmark, Estonia, France, Greece, Ireland, Italy, Norway and the United Kingdom (Scotland). Data for Spain are not displayed here but are available through the Acuivisor: https://servicio.pesca.mapama.es/acuivisor/. Data in other EU Member States are not available.
EMODnet Human Activities, Aquaculture, Freshwater

The freshwater production dataset in the European waters and countries was created in 2017 by AND-International for the European Marine Observation and Data Network (EMODnet). The dataset provides information about the location of freshwater finfish farms in the EU and partner countries where data are available. The dataset is available for viewing and download on EMODnet web portal (Human Activities, https://emodnet.ec.europa.eu/en/human-activities). For EU MSs, it relies mainly on data collected under the Regulation (EU) 2016/429 (the ‘Animal Health Law’). As far as partner countries are concerned, data were collected in Norway and in the UK (Scotland only), where detailed data are provided online. Data have been collected in Austria, Belgium, Czechia, Denmark, Estonia, France, Greece, Ireland, Lithuania, Norway, Poland, Slovenia, and the UK (Scotland only). Most important producing countries where data are missing are Spain, Italy, Bulgaria, Germany, Hungary and Romania. Data for Spain are available through the Acuivisor, through the following link: https://servicio.pesca.mapama.es/acuivisor/. Each point has the following attributes (where available): country, owner name, species from Source (English translation of the information provided on species provided in the source), farm type (Carp, Diversified pond fish, Eel, Salmonids, Sturgeon, Other, n/a), production stage (Grow out for human consumption, Hatchery, Nursery, Broodstock, Put and take fisheries, Restoration of wild stock, Processing facility, Other, n/a), production method (Cages/Enclosures/Pens, Closed systems (recirculation), Ponds, Tanks/Raceways, Quarantine facility, Research facility, Other, n/a), purpose (Commercial, Restocking, Education, Other, n/a), point information (Polygon centroid, Original) depending on how the information is provided in the source (polygons or points), site_id and source_id (id from the source where available). The farm type relies on a typology established by AND-International, based on available information on the species reared in the different production sites. A relational table provides harmonised information about the reared species using Eurostat nomenclature for the Species Group (Carps, barbels and other cyprinids; Miscellaneous freshwater fishes; River eels; Salmons, trouts, smelts; Sturgeons, paddlefishes; Tilapias and other cichlids), the species name (commercial and scientific) and the code. Data in EMODnet have been updated in 2025, using data updated as of 2022 for Lithuania, 2024 for Estonia, Greece and Poland and 2025 for other countries.
PANGAEA - Data from quaternary environment of the Eurasian North (QUEEN)

Dataof QUEEN in PANGAEA comprise results from analysis of marine sediments, ice cores, profiles through periglacial deposits and lacustrine sediments as well as modelled and reconstruced environmental data.
Under the umbrella of the ESF, the programme QUEEN (Quaternary Environment of the Eurasian North) aims to combine information obtained by Russian and Western projects to provide a common picture of present and past environmental changes across the whole Arctic. Regions of particular importance for understanding the Arctic's role in global climate change are the Eurasian shelves and the land masses south of these, including Siberian permafrost. The ice sheets in these regions are key elements in paleoclimatic models and play a vital role in the reconstruction of a continuos paleoenvironmental record. Special effort is devoted to the correlation of records from different sources across the Arctic.
Black Sea - DIVA 4D 6-year seasonal analysis of Water body phosphate 1970/2018 v2021

Moving 6-year analysis of Water_body_phosphate in the Black Sea for each season: spring (March-May), summer (June-August), autumn (September-November), winter (December-February). Every year of the time dimension corresponds to the 6-years centred average of each season. 
6-years periods span: from 1970-1975 until 2013-2018
Depth range (IODE standard depths): -200.0, -150.0, -125.0, -100.0, -75.0, -50.0,-40.0, -30.0, -20.0, -10.0, -5.0, -0.0. 
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 1min topography is used for the contouring preparation. Analysed field masked using relative error threshold 0.3 and 0.5 DIVA settings: signal-to-noise ratio and correlation length were estimated using data mean distance as a minimum (for L) and vertically filtered. Log transformation  was used in the analyses. Background field: the data mean value is subtracted from the data. Detrending of data: no, Advection constraint applied: no. Units: umol/l.
Happywhale - False Killer Whale in North Atlantic Ocean

Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales.
Original provider: Happywhale Dataset credits: Happywhale and contributors Supplemental information: Sightings and images were submitted to Happywhale by contributors. A portion of the Happywhale data were transferred to OBIS-SEAMAP upon the agreement between Happywhale and OBIS-SEAMAP. There may be duplicate records among Happywhale datasets and other OBIS-SEAMAP datasets. The precision of date/time vary per record. Some records have date accuracy up to year only. This dataset includes sightings and photos from the following 2 contributors in alphabetic order: Marilia Olio; Mike Greenfelder