The BenthOBS dataset includes long-term time series on marine benthic macrofauna, since 1967, along the whole French metropolitan coast. It includes 20 sampling location. BenthOBS aims to establish a national network for the observation of macrozoobenthos. In a context of global change, It is essential to have time series capable of highlighting and understanding ongoing changes in the specific diversity within communities and their consequences on the functioning of marine ecosystems. The BenthOBS network provides the scientific community and stackers with validated data on the following parameters: specific abundance, sediment size composition, sediment organic matter, sediment C content, sediment N content.

Plankton was sampled with a Continuous Underway Fish Egg Sampler (CUFES, 315µm mesh size) at 4 m below the surface, and a WP2 net (200µm mesh size) from 100m to the surface, or 5 m above the sea floor to the surface when the depth was < 100 m, in the Bay of Biscay. The full images were processed with the ZooCAM software and the embedded Matrox Imaging Library (Colas et a., 2018) which generated regions of interest (ROIs) around each individual object and a set of features measured on the object. The same objects were re-processed to compute features with the scikit-image library http://scikit-image.org. The 1, 286, 590 resulting objects were sorted by a limited number of operators, following a common taxonomic guide, into 93 taxa, using the web application EcoTaxa http://ecotaxa.obs-vlfr.fr. For the purpose of training machine learning classifiers, the images in each class were split into training, validation, and test sets, with proportions 70%, 15% and 15%. The archive contains : taxa.csv.gz Table of the classification of each object in the dataset, with columns : - objid : unique object identifier in EcoTaxa (integer number). - taxon_level1 : taxonomic name corresponding to the level 1 classification - lineage_level1 : taxonomic lineage corresponding to the level 1 classification - taxon_level2 : name of the taxon corresponding to the level 2 classification  - plankton : if the object is a plankton or not (boolean) - set : class of the image corresponding to the taxon (train : training, val : validation, or test) - img_path : local path of the image corresponding to the taxon (of level 1), named according to the object id features_native.csv.gz Table of morphological features computed by ZooCAM. All features are computed on the object only, not the background. All area/length measures are in pixels. All grey levels are in encoded in 8 bits (0=black, 255=white). With columns : - area : object's surface - area_exc : object surface excluding white pixels - area_based_diameter : object's Area Based Diameter: 2 * (object_area/pi)^(1/2) - meangreyobjet : mean image grey level - modegreyobjet : modal object grey level - sigmagrey : object grey level standard deviation - mingrey : minimum object grey level - maxgrey : maximum object grey level - sumgrey : object grey level integrated density: object_mean*object_area - breadth : breadth of the object along the best fitting ellipsoid minor axis - length : breadth of the object along the best fitting ellipsoid majorr axis - elongation : elongation index: object_length/object_breadth - perim : object's perimeter - minferetdiam : minimum object's feret diameter - maxferetdiam : maximum object's feret diameter - meanferetdiam : average object's feret diameter - feretelongation : elongation index: object_maxferetdiam/object_minferetdiam - compactness : Isoperimetric quotient: the ration of the object's area to the area of a circle having the same perimeter - intercept0, intercept45 , intercept90, intercept135 : the number of times that a transition from background to foreground occurs a the angle 0ø, 45ø, 90ø and 135ø for the entire object - convexhullarea : area of the convex hull of the object - convexhullfillratio : ratio object_area/convexhullarea - convexperimeter : perimeter of the convex hull of the object - n_number_of_runs : number of horizontal strings of consecutive foreground pixels in the object - n_chained_pixels : number of chained pixels in the object - n_convex_hull_points : number of summits of the object's convex hull polygon - n_number_of_holes : number of holes (as closed white pixel area) in the object - roughness : measure of small scale variations of amplitude in the object's grey levels - rectangularity : ratio of the object's area over its best bounding rectangle's area - skewness : skewness of the object's grey level distribution - kurtosis : kurtosis of the object's grey level distribution - fractal_box : fractal dimension of the object's perimeter - hist25, hist50, hist75 : grey level value at quantile 0.25, 0.5 and 0.75 of the object's grey levels normalized cumulative histogram - valhist25, valhist50, valhist75 : sum of grey levels at quantile 0.25, 0.5 and 0.75 of the object's grey levels normalized cumulative histogram - nobj25, nobj50, nobj75 : number of objects after thresholding at the object_valhist25, object_valhist50 and object_valhist75 grey level - symetrieh :index of horizontal symmetry - symetriev : index of vertical symmetry - skelarea : area of the object skeleton - thick_r : maximum object's thickness/mean object's thickness - cdist : distance between the mass and the grey level object's centroids features_skimage.csv.gz Table of morphological features recomputed with skimage.measure.regionprops on the ROIs produced by ZooCAM. See http://scikit-image.org/docs/dev/api/skimage.measure.html#skimage.measure.regionprops for documentation. inventory.tsv Tree view of the taxonomy and number of images in each taxon, displayed as text. With columns : - lineage_level1 : taxonomic lineage corresponding to the level 1 classification - taxon_level1 : name of the taxon corresponding to the level 1 classification - n : number of objects in each taxon group map.png Map of the sampling locations, to give an idea of the diversity sampled in this dataset. imgs Directory containing images of each object, named according to the object id objid and sorted in subdirectories according to their taxon.

Based on the consolidation of the Ifremer networks RESCO (https://doi.org/10.17882/53007) and VELYGER (https://doi.org/10.17882/41888), the general objective of the ECOSCOPA project is to analyze the causes of spatio-temporal variability of the main life traits (Larval stage - Recruitment - Reproduction - Growth – Survival – Cytogenetic anomalies) of the Pacific oyster in France and follow their evolution over the long term in the context of climate change. The high frequency environmental data are monitored since 2010 at several stations next to oyster farm areas in eight bays of the French coast (from south to north): Thau Lagoon and bays of Arcachon, Marennes Oléron, Bourgneuf, Vilaine, Brest, Mont Saint-Michel and Veys (see map below). Sea temperature and practical salinity are recorded at 15-mins frequency. For several sites, fluorescence and turbidity data are also available. Data are acquired with automatic probes directly put in oyster bags or fixed on metallic structure at 50 cm over the sediment bottom, except for Thau Lagoon whose probes are deployed at 2m below sea surface. Since 2010, several types of probes were used: STP2, STPS, SMATCH or WiSens CTD from NKE (www.nke-instrumentation.fr) and recently ECO FLNTU (www.seabird.com). The probes are regularly qualified by calibrations in the Ifremer coastal laboratories. Precision estimated of the complete data collection process is: temperature (±0.1°C), salinity (±0.5psu), in vivo fluorescence (±10%), turbidity (±10%). The data are qualified into several levels: 0-No Quality Check performed, 1-Good data, 2-Probably good data, 3-Probably bad data, 4-Bad data, 5-Value changed, 7-Nominal value, 8-Interpolated value, 9-Missing value. 

The main objective of the SWIM Level 2S (L2S) product is to provide along-track directional wave spectra measures, as well as the integrated parameters of the associated wave systems (wave length, significant wave height, direction), over the global ocean, as observed with SWIM instrument onboard CFOSAT. CFOSAT (Chinese French Ocean SATellite) is a french-chinese mission launched in 2018, whose aim is to provide wind (SCAT instrument) and wave (SWIM instrument) measurements over the sea surface. The wave spectra and their associated partitions are provided independently for each SWIM incidence (from 2° to 10°), together with the sigma0 resampled at a 20m resolution. They are complemented with information from the nadir beam such as the sigma0, wind speed, significant wave height or rain flag. The SWIM level 2S (L2S) product is generated in delayed mode, a few days after acquisition. It complements the Near-Real Time (NRT) L2 product delivered by the CWWIC center by providing an alternative and evolutive processing to test and implement quickly new algorithms for the wave inversion over the whole mission archive. These evolutions may take advantage of better ancillary data not available in NRT (ice mask product, best estimates of wind or wave model), of the combination with wind measurements from the onboard SCAT scatterometer. The product is also designed to handle complex situations such as coastal areas and heterogeneous seas. These complex situations are by nature of particular scientific interest (e.g. wind wave interactions, wave evolution in coastal region). This version 2 improves the previous release in particular through a new empirical modulation transfer function (MTF) and better partitioning. The dataset is also lighter in size. It has been completely reprocessed from SWIM Level 1 archive. Note that the dataset is split on the access server in two different sub-versions (**2.0** for the L2S using Level 1 in OP06 version, **2.1** for the L2S using Level 1 in OP07 version). No major differences are expected. The SWIM L2S product is generated and distributed by Ifremer / CERSAT in the frame of the Ifremer Wind and Wave Operation Center (IWWOC) co-funded by Ifremer and CNES and dedicated to the processing of the delayed mode data of CFOSAT mission.

Serveur wms public de l'Ifremer - projet REPAMO

The DBCP – Data Buoy Cooperation Panel - is an international program coordinating the use of autonomous data buoys to observe atmospheric and oceanographic conditions, over ocean areas where few other measurements are taken. DBCP coordinates the global array of 1 600 active drifting buoys (August 2020) and historical observation from 14 000 drifting buoys. Data and metadata collected by drifting buoys are publically available in near real-time via the Global Data Assembly Centers (GDACs) in Coriolis-Ifremer (France) and MEDS (Canada) after an automated quality control (QC). In long term, scientifically quality controlled delayed mode data will be distributed on the GDACs. Disclaimer: the DB-GDAC is under construction. It is currently (January 2020) aggregating data from the Coriolis DAC (E-Surfmar, Canada). Additional DACs are considered. An interim provision from GTS real-time data to GDAC may be provided from Coriolis DAC.  

The COriolis Ocean Dataset for Reanalysis (hereafter "CORA") product is a global dataset of in situ temperature and salinity measurements. The CORA observations comes from many different sources collected by Coriolis data centre in collaboration with the In Situ Thematic Centre of the Copernicus Marine Service (CMEMS INSTAC).  The observation integrated in the CORA product have been acquired both by autonomous platforms (Argo profilers, fixed moorings , gliders , drifters, sea mammals) , research or opportunity vessels (CTDs, XBTs, ferrybox).  From the near real time CMEMS In Situ Thematic Centre product validated on a daily and weekly basis for forecasting purposes, a scientifically validated product is created. It s a "reference product" updated on a yearly basis since 2007. This product has been controlled using an objective analysis (statistical tests) method and a visual quality control (QC). This QC procedure has been developed with the main objective to improve the quality of the dataset to the level required by the climate application and the physical ocean re-analysis activities. It provides T and S weekly gridded fields and individual profiles both on their original level with QC flags and interpolated level. The measured parameters, depending on the data source, are : temperature, salinity. The reference level of measurements is immersion (in meters) or pressure (in decibars).  CORA contains historical profiles extracted from the EN.4 global T&S dataset, World Ocean Atlas, SeaDataNet, ICES and other data aggregators . The last version of the CORA product are also available freely from the Copernicus WEB site :   - Global Ocean- CORA- In-situ Observations Yearly Delivery in Delayed Mode - Global Ocean- Delayed Mode gridded CORA- In-situ Observations objective analysis in Delayed Mode  

ROCCH, the French Chemical Contaminant Monitoring Network, regularly provides data for assessing the chemical quality of French coastal waters. Concentrations of trace metals and organic compounds are measured in integrative matrices (bivalves and sediments). Surface sediment samples are collected from 200 to 250 monitoring stations in the English Channel, the Bay of Biscay and Mediterranean lagoons every six years. Results concerning approximately 140 historical and emerging chemical substances (metals, PAHs, PCBs, PBDEs, PFAS …) are submitted to international databases of the Regional Sea Convention (OSPAR for the North East Atlantic and the Barcelona Convention for the Mediterranean) and disseminated to public stakeholders. During the ROCCHSED campaign in spring 2022, three sediment cores, each forty to fifty centimetres long, were collected from three different sites in the Bay of Biscay. Horizons of one to two centimetres in length were dated, sieved and freeze-dried for chemical analysis. The concentrations of metals, PAHs and PCBs were determined in horizons aged from over 150 years to the present in order to define the reference concentration of natural levels and describe the temporal profile of contamination.

To deliver the best Argo data to users in the simplest way, No QC flags; No data mode; No manuals - Just straight forward good data The Argo program provides an unprecedented volume of oceanographic data, yet its operational complexity — involving multiple data modes, quality control flags, and metadata conventions — often hinders its direct usage. The EasyOneArgo initiative addresses this challenge by delivering simplified, high-quality subsets of Argo data, specifically designed to streamline user access and integration. We introduce two core products: EasyOneArgoTS, a curated selection of temperature-salinity profiles filtered by strict quality criteria and optimized across real-time, adjusted, and delayed modes; and EasyOneArgoTSLite, its vertically interpolated counterpart standardized over 102 pressure levels. Each profile is packaged as a standalone CSV file with structured metadata, and indexed for seamless retrieval. Visual comparisons reveal clear advantages in usability and consistency, notably between raw and interpolated datasets. The approach is being extended to biogeochemical variables via EasyOneArgoBGC and EasyOneArgoBGCLite, currently under development. EasyOneArgo products are publicly available through monthly FAIR-compliant releases and invite community feedback for continued refinement. This work represents a user-centric shift in Argo data delivery: no flags, no manuals — just clean, structured ocean data ready for immediate scientific application.  

The SOMLIT-SOGIR time-series data characterize the hydrology of the Gironde Estuary ecosystem, located in the South-western France and flowing into the Bay of Biscay. Monthly-like measurements have been undertaken since 1997 by the OASU and EPOC teams (Univ. Bordeaux/CNRS). The SOMLIT-SOGIR time series is a part of the French monitoring network SOMLIT (https://www.somlit.fr/), labelled by the CNRS as a national Earth Science Observatory (Service National d’Observation : SNO). It aims to detect the long-term evolution of monitored ecosystems including both natural and anthropogenic forcings. Implemented at three sites (PK 30: 45.06833°N, 0.63833°W; PK 52: 45.24667°N, 0.725°W; PK 86:  45.5167°N, 0.95°W), the SOMLIT-SOGIR time series is among the oldest long-term coastal observation time series of the French Research Infrastructure dedicated to coastal ocean observations (RI ILICO, https://www.ir-ilico.fr). SOMLIT-SOGIR samples are collected at 1m below the water surface and 1m above the floor, at high and low tide, during slack water. Samples collected are analysed for 15 core parameters: water temperature and salinity, dissolved oxygen, pH, ammonia, nitrate, nitrite, phosphate, silicic acid, suspended particulate matter, particulate organic carbone, particulate nitrogen, chlorophyll a, delta15N and delta13C. CTD-PAR-profile is also performed at site PK86 during high tide. The SOMLIT network quality management system is in line with the ISO/IEC 17025:2017 standard: “General requirements for the competence of testing and calibration laboratories”. Further information on standard operating procedures for sample collection and data acquisition are available at: https://www.somlit.fr/parametres-et-protocoles. For more information on the quality flagging scheme: https://www.somlit.fr/codes-qualite/.