Le 14 mars 2017, un décret fixant un socle de données de référence mis à disposition par le service public est promulgué. Il entre en vigueur le 1er avril 2017. Ce décret est issu de l’article 14 de la LOI n° 2016-1321 du 7 octobre 2016 « pour une République numérique » dite « loi Lemaire ». Le décret a arrêté 9 données de références : - La Base Adresse Nationale (BAN) - Le Code Officiel Géographique (COG) - Le Plan Cadastral Informatisé (PCI) - Le Référentiel de l'organisation administrative de l'Etat - Le Référentiel à Grande Echelle (RGE) - Le Répertoire National des Associations (RNA) - Le Répertoire Opérationnel des Métiers et des Emplois (ROME) - Le Registre Parcellaire Graphique (RPG) : contours des îlots culturaux et leur groupe de cultures majoritaire - La base Sirene des entreprises et de leurs établissements (SIREN, SIRET) Le décret d’application 2017-3315 du 14 mars 2017 relatif au service public fixe la mise à disposition de ces données de référence en vue de faciliter leur réutilisation. Ces 9 données de références ont été choisis par rapport à leur fort impact économique et social. Le 14 juin 2017, un arrêté du Premier Ministre fixe le format, la description et les modalités de mise à disposition (voir lien URL). --- 3 types de licence concernent les bases de données diffusées en open data : - Licence Ouverte (LO): élaborée par la mission Etalab. Décret 2017 la désigne comme licence de référence pour les administrations pour la publication données publiques. Réutilisation large car autorise la reproduction, redistribution, l'adaptation et exploitation commerciale des données. Compatible avec les standards des licences Open Data internationaux. Obligation de mentionner la paternité (source : nom du "concédant" et date de dernière MAJ de la donnée ou renvoi lien URL vers la source d'information) - Licence ODbL: autorise à copier, distribuer, utiliser la BDD, produire des créations à partir de cette BDD et modifier, transformer, construire à partir de cette BDD. Obligation de mentionner la source des données, partager à l'identique les BDD dérivées, garder ouvertes ces données. Les données proposées sous cette licence sont similaires à celle de la licence d'en-dessous mais le libellé à la norme AFNOR et d'acheminement ne sont pas disponibles. Les données subissent des traitements de qualité supplémentaires. - Licence gratuite de repartage: autorise à copier, distribuer, utiliser la BDD et produire des créations à partir de cette BDD, modifier, transformer et construire à partir de cette BDD. Obligation de mentionner la source, ne pas commercialiser la donnée, communiquer à IGN et La Poste des bases dérivées et leur céder les droits d'auteurs et de propriété industrielle.

The in-situ TAC integrates and quality control in a homogeneous manner in situ data from outside Copernicus Marine Environment Monitoring Service (CMEMS) data providers to fit the needs of internal and external users. It provides access to integrated datasets of core parameters for initialization, forcing, assimilation and validation of ocean numerical models which are used for forecasting, analysis and re-analysis of ocean physical and biogeochemical conditions. The in-situ TAC comprises a global in-situ centre and 6 regional in-situ centres (one for each EuroGOOS ROOSs). The focus of the CMEMS in-situ TAC is on parameters that are presently necessary for Copernicus Monitoring and Forecasting Centres namely temperature, salinity, sea level, current, waves, chlorophyll / fluorescence, oxygen and nutrients. The initial focus has been on observations from autonomous observatories at sea (e.g. floats, buoys, gliders, ferrybox, drifters, and ships of opportunity). The second objective was to integrate products over the past 25 to 50 years for re-analysis purposes... Gathering data from outsider organisations requires strong mutual agreements. Integrating data into ONE data base requires strong format standard definition and quality control procedures. The complexity of handling in situ observation depends not only on the wide range of sensors that have been used to acquire them but, in addition to that, the different operational behaviour of the platforms (i.e vessels allow on board human supervision, while the supervision of others should be put off until recovering or message/ping reception)°

Temporal series (annual mean values) and long term average (LTA) of temperature for each river mouth.

The Surface Ocean CO₂ Atlas (SOCAT) is a synthesis activity for quality-controlled, surface ocean fCO₂ (fugacity of carbon dioxide) observations by the international marine carbon research community (>100 contributors). SOCAT data is publicly available, discoverable and citable. SOCAT enables quantification of the ocean carbon sink and ocean acidification and evaluation of ocean biogeochemical models. SOCAT represents a milestone in biogeochemical and climate research and in informing policy. SOCAT data are released in versions. Each succeeding version contains new data sets as well as updates of older ones. The first version of SOCAT was released in 2011, the second and third version followed biennially. Automation allowed annual public releases since version 4. The latest SOCAT version (version 5) has 21.5 million observations from 1957 to 2017 for the global oceans and coastal seas. SOCAT contains data from the VOS, OceanSites network and mooring, buoy data in general as well as calibrated sensor data.

Calculation of the average annual sediment balance per stretch of coast for the past 50 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.

Nature de l'occupation du sol par commune et en m².

Localisation et description des sentiers de randonnées (GR, PDIPR, itinérance à pied, chemin local,sans classement). Localisation et description des tronçons (accessibilité/nature du sol/état...). Bornes/mats (description/état/historique des interventions...) Mobiliers (description/état/historique des interventions...)

The eleven collected wild strains of T. lutea were compared phenotypically, in particular with regard to their pigment and lipid profiles. The genome of each T. lutea strain was also sequenced to investigate the genetic structure and genome organisation of this species. Collected data were summarized in a genome browser to provide easy-to-use support for the scientific community (https://genomes-catalog.ifremer.fr). This provides an important resource- to understand, exploit and predict the biodiversity of this species.

Combined product of Water body ammonium 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 ammonium product is masked using the relative error threshold 0.5. Units: umol/l.

The SeaDataNet aggregated datasets over the Atlantic Ocean are regional ODV historical collections of all temperature and salinity measurements contained within SeaDataNet database and covering 3 European sea basins: North Arctic Ocean, North Sea, North Atlantic Ocean. Two versions have been published during SeaDataNet 2 and they represent a snapshot of the SeaDataNet database content at two different times: • V1.1 January 2014 • V2 March 2015 Each of them is the result of the Quality Check Strategy (QCS) implemented during SeaDataNet 2 that contributed to highly improve the quality of temperature and salinity data. The QCS is made by four main phases: 1. data harvesting from the central CDI 2. file and parameter aggregation 3. quality check analysis at regional level 4. analysis and correction of data anomalies. The aggregated datasets have been prepared and quality checked using ODV software.