The European Tracking Network (ETN) aims at bringing together marine researchers based in Europe that use aquatic biotelemetry as a tool. The main goals of the network are the promotion of transboundary cooperation, the establishment of a pan-European aquatic telemetry infrastructure network, improved data sharing through a central data portal and enhanced funding opportunities. ETN is co-coordinated by IMAR/University of the Azores and the Canadian Ocean Tracking Network (OTN) initiative. ETN is a partner node of OTN. The central data platform is hosted by the Flanders Marine Institute (VLIZ) and provides three key services to the users. 1) Data and metadata are stored centrally at a PostgreSQL database. To facilitate the data entry and data management for the users, a web application was developed in PHP using Symfony framework. 2) A data explorer is available to visualize the data. Datasets can be filtered based on area, species or time frame. In addition, detection data can be linked to other data types ( (e.g. moon index and tides) and several plot options are available. 3) In the R-studio environment, more detailed analyses can be performed.

The three digital maps provided in this product aim to assess the degree of Offshore windfarm siting suitability existing over a geographical area with a focal point where waters of France and Spain meet in Biscay Bay on 500 m depth. The maps display respectively the spatial distribution of the average and lowest windfarm siting suitability scores along with the average wind speed distribution over a time period of 10 years. They are part of a process set up to assess the fit for use quality of the currently available datasets to support a preliminary selection of potential offshore sites for wind energy development. To build these maps, GIS tools were applied to several key spatial datasets from the 5 data type domains considered in the project: Air, Marine Water, Riverbed/Seabed, Biota/Biology and Human Activities, collated during the initial stages of the project. Initially, each selected dataset was formatted and clipped to the study area extent and spatially classified according to suitability scores, to define raster layers with the variables depicting levels of current anthropogenic and environmental spatial occupation of activities, seabed depth and slope, distances to shoreline, shipping intensity, mean significant wave height, and substrate type. These pre-processed layers were employed as inputs for applying a spatial multi-criteria model using a wind farming suitability classification based on a discrete 5 grades index, ranging from Very Low up to Very High suitability. In adition to suitability maps, an average wind speed spatial distribution map for a 10 years period, at 10 m height, was obtained over the study area from the raster processing of a wind speed time series of monthly means available from daily wind analysis data. The characteristics of the datasets used in this exercise underwent an appropriateness evaluation procedure based on a comparison between their measured quality and those specified for the product. The study area, located in the Biscay Golf includes a coastal zone of Spain and France. Consequently, some zones are subject to constraints to offshore windfarm implementation due to environmental protection, visual impacts and seafoor attributes. Data gaps exist with an emphasis on fishing activity and distribution of essential habitats and species. All the spatial information made available in these maps and from the subsequent appropriateness analysis of the datasets, contributes to a clearer overview of the amount of public-access baseline knowledge currently existing for the North Atlantic basin area.

Temporal series (annual mean values) and Long Term Average (LTA) of sediment load for each river mouth where in situ data is available. Different sources can be mixed if any.

Calculation of the average annual sediment balance per stretch of coast for the past 100 years for all coastal zones bordering the North Atlantic Ocean. For this scale of study, this has been interpreted in terms of shoreline advance / retreat in mm/year. Required data sources are therefore national or international datasets giving this parameter directly. It is also possible to utilise more aggregated data sources, but annual values would then be approximated from them. The main challenge in producing this product lies with obtaining datasets which include this data from multiple countries and potentially multiple languages, since this data is usually produced as a result of comparatively small scale studies.

Cartographie historique des écluses à poissons sur l'île de Ré.

Sit@del2 est la base de données du système statistique public relative à la construction neuve de logements et de locaux non résidentiels. Cette base est alimentée par les informations des permis de construire, permis d’aménager, permis de démolir et déclarations préalables. Ces données sont transmises chaque mois par les centres instructeurs des directions départementales de l’équipement et par les communes (ou groupements de communes) autonomes.

The Global Sea Level Observing System (GLOSS) was established by the Intergovernmental Oceanographic Commission (IOC) of UNESCO in 1985 to establish a well-designed, high-quality in situ sea level observing network to support a broad research and operational user base. Various tide gauge networks have contributed to GLOSS, each with a different focus and each changing over time as research priorities evolve. The main component is the GLOSS Core Network (GCN), a global set of ~300 tide gauges that serves as the backbone of the global in situ sea level network. GCN gauges were allocated to each island or group of islands at intervals not closer than 500 km, and along continental coasts at intervals generally not less than 1000 km. Preference was given to islands in order to maximise exposure to the open ocean. Established in 1933, the Permanent Service for Mean Sea Level (PSMSL) is responsible for the collection, publication, analysis and interpretation of sea level data from the global network of tide gauges, including the GLOSS Core Network.

Combined product of Water body silicate based on DIVA 4D 10-year analysis on five regions : Northeast Atlantic Ocean, North Sea, Baltic Sea, Black Sea, Mediterranean Sea. The boundaries and overlapping zones between these five regions were filtered to avoid any unrealistic spatial discontinuities. This combined water body silicate product is masked using the relative error threshold 0.5. Units: umol/l

The International Council for the Exploration of the Sea (ICES), is a global organization that develops science and advice to support the sustainable use of the oceans. ICES is a network of more than 5,000 scientists from over 690 marine institutes in 20 member countries and beyond. 1,500 scientists participate in our activities annually. ICES has a well-established Data Centre, which manages a number of large dataset collections related to the marine environment. The majority of data – covering the Northeast Atlantic, Baltic Sea, Greenland Sea, and Norwegian Sea – originate from national institutes that are part of the ICES network. The ICES Data Centre provides marine data services to ICES member countries, expert groups, world data centres, regional seas conventions (HELCOM and OSPAR), the European Environment Agency (EEA), Eurostat, and various other European projects and biodiversity portals. ICES aims to provide all data collections online and according to the ICES Data policy, which enables open access to all data that are do not fall under specific commercial or personal privacy concerns.

Calculation of the average annual sediment balance per stretch of coast for the past 10 years for all coastal zones bordering the North Atlantic Ocean. For this scale of study, this has been interpreted in terms of shoreline advance / retreat in mm/year. Required data sources are therefore national or international datasets giving this parameter directly. It is also possible to utilise more aggregated data sources, but annual values would then be approximated from them. The main challenge in producing this product lies with obtaining datasets which include this data from multiple countries and potentially multiple languages, since this data is usually produced as a result of comparatively small scale studies.