AndreaBozzo/ceres-open-data-index huggingface dataset:
Données statistiques sur les caractéristiques des invalides

La DREES et l'Institut des politiques publiques (IPP) publient des données sur les caractéristiques des invalides issues de l’exploitation du volet invalidité de l’EIR : âge d’entrée en invalidité, durée passée en invalidité, niveau de diplôme. L’échantillon interrégimes de retraités (EIR), réalisé tous les quatre ans par la DREES, est un rapprochement de données administratives comprenant l’ensemble des droits à retraite acquis dans les différents régimes français pour un échantillon représentatif d’assurés. Dans le cadre de la huitième vague de cette opération statistique qui porte sur la situation au 31 décembre de l'année N (2016 ou 2020), l’EIR comprend pour la première fois des informations concernant les pensions d’invalidité des bénéficiaires du régime général. Ces nouvelles données individuelles contiennent des éléments détaillées sur les effectifs des bénéficiaires d’une pension d’invalidité, les âges d’entrée dans le dispositif, les effectifs par type d’invalidité ou encore les montants de pensions d’invalidité perçus selon le régime de retraite, le sexe et le type d’invalidité. L’appariement de l’EIR – invalidité à l’échantillon démographique permanent (EDP) de l’INSEE permet par ailleurs de mieux connaître cette population en ce qui concerne le niveau d’éducation et la situation familiale.
Secondary Network (SPEN_015) Data Quality Checks

This data table provides the detailed data quality assessment scores for the Secondary Network dataset. The quality assessment was carried out on the 19th February 2026. At SPEN, we are dedicated to sharing high-quality data with our stakeholders and being transparent about its' quality. This is why we openly share the results of our data quality assessments. We collaborate closely with Data Owners to address any identified issues and enhance our overall data quality; to demonstrate our progress we conduct annual assessments of our data quality in line with the dataset refresh rate. To learn more about our approach to how we assess data quality, visit [Data Quality - SP Energy Networks]. We welcome feedback and questions from our stakeholders regarding this process. Our Open Data Team is available to answer any enquiries or receive feedback on the assessments. You can contact them via our Open Data mailbox at [opendata@spenergynetworks.co.uk]. The first phase of our comprehensive data quality assessment measures the quality of our datasets across three dimensions. Please refer to the data table schema for the definitions of these dimensions. We are now in the process of expanding our quality assessments to include additional dimensions to provide a more comprehensive evaluation and will update the data tables with the results when available. ### Disclaimer The data quality assessment may not represent the quality of the current dataset that is published on the Open Data Portal. Please check the date of the latest quality assessment and compare to the 'Modified' date of the corresponding dataset. The data quality assessments will be updated on either a quarterly or annual basis, dependent on the update frequency of the dataset. This information can be found in the dataset metadata, within the Information tab. If you require a more up to date quality assessment, please contact the Open Data Team at [opendata@spenergynetworks.co.uk] and a member of the team will be in contact.
Performance Contract Indicators

In the performance contract of Infrabel (Dutch: [performantiecontract], French: [contrat de performance]), approved by the Council of Ministers on 23/12/2022, which covers the period 2023-2032, a chapter is dedicated to the process of monitoring and continuous improvement of Infrabel's performance. This process is an agreement between Infrabel, the minister responsible for Mobility, and the Federal Department of Mobility and Transport. The monitoring of these performances is carried out using various tools, depending on the nature of the objectives: * Quantitative measurements (indicator or KPI) that allow the execution of the performances and the quality of the services provided to be measured. * Reports that provide a textual summary of the execution of the performances and the quality of the services provided. * Remediation plans. Once a year, the Federal Department for Mobility and Transport organizes a performance dialogue. This takes place latest on June 30th of the year following the year to which the analysis of the indicators/reports pertains. The main goal of the performance dialogue is to evaluate whether the intended results for the performance indicators have been achieved and whether other contractual obligations have been fulfilled. To this end, the Department for M&T receives a report on the evolution of the indicators, whose values for year Y are calculated on March 31st of year Y+1. These values are included by the Department for M&T in the annual public report ([Dutch] / [French]) on the performance dialogue. The "table" and "dashboard" tabs of this dataset contain the values included in the public report of the Federal Department for Mobility and Transport for the indicators of the performance contract, which are of two types: 1. The performance indicators, which measure performance against the quantitative targets that Infrabel must achieve in the contract: * Target values for the target year 2027 * Target values for the target year 2032 * Annual intermediate progress values for the years 2023 to 2027 * Remediation thresholds that trigger the drafting of remediation plans (when not achieved for two consecutive years) * Bonus thresholds that may entitle Infrabel to a financial bonus (when results exceed expectations) 2. The informative indicators, which are not subject to a quantitative commitment in the contract. Note The official publication via the Federal Department occurs in both Dutch and French. Since no official English publication exists, the translations on this page are limited to the description of the data. This is done in order to improve the reading experience, but bears no official meaning. Category and subcategory labels are pertained in French and Dutch.
Enveloppes de la taxe GEMAPI en Pays de la Loire

Depuis 2018, les compétences de GEstion des Milieux Aquatiques et Prévention des Inondations (GEMAPI) relèvent des EPCI, qui peuvent financer certaines opérations par la levée d'une taxe spécifique : la taxe GEMAPI. Ce jeu de données regroupe les informations présentées dans le PowerBI de l'article "La taxe GEMAPI en Pays de la Loire" partagé sur le site de TEO : [https://teo-paysdelaloire.fr/tableau-de-bord/la-taxe-gemapi-en-pays-de-la-loire/] La colonne "Comptabilité GEMAPI" provient du jeu de données "Balances comptables des groupements à fiscalité propre" disponible sur l'opendata du ministère de l'économie (https://data.economie.gouv.fr/pages/accueil/). TEO a sélectionné les comptes correspondant à la GEMAPI (7346 et 73136) des nomenclatures M14 et M57. Les données sont disponibles jusqu'à l'année N-2 Les valeurs de population sont issu des données officielles de l'INSEE à l’échelle des communes et agrégées par EPCI. Les années 2023 et 2024 ont des valeurs de population estimée, calquées sur les taux d'augmentation des années précédentes
Input of continuous anthropogenic sound in Europe Seas, Jan. 2020

[Lien vers la fiche source] This raster dataset represents the input of continuous anthropogenic sound in the European Seas. Continuous anthropogenic underwater noise is found in the entire European marine area and is mainly produced by maritime traffic. As no thresholds for pressure have been agreed yet, even areas of low or infrequent maritime traffic are included as pressures. This dataset uses shipping density as a representation of distribution of continuous underwater noise. This dataset is based on a truncated version of the EMODnet (Automatic Identification System) AIS based vessel density dataset for 2017 (all ships, year average). The vessel density was rescaled from a 1 km to 10 km resolution (mean values) using the EEA 10 km grid. The dataset has been transformed to a logarithmic scale (ln1). This dataset has been prepared for the calculation of the combined effect index, produced for the ETC/ICM Report 4/2019 "Multiple pressures and their combined effects in Europe's seas" available on: https://www.eionet.europa.eu/etcs/etc-icm/etc-icm-report-4-2019-multiple-pressures-and-their-combined-effects-in-europes-seas-1.
Assessment of contamination status using CHASE+ excluding PBDEs, Mar. 2019

[Lien vers la fiche source] This dataset presents the resulting assessment grid (based on the EEA reference grid) with the classification of chemical status of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD). This classification has been performed using the CHASE+ tool, with classifications of the matrices ‘water’, ‘sediment’ and ‘biota’ and indicators of ‘biological effects’, as well as an integrated classification of chemical status, combining results of all matrices. The chemical status is evaluated in five classes, where NPAhigh and NPAgood are recognised as ‘non-problem areas’ and PAmoderate, PApoor and PAbad are recognised as ‘problem areas’. This is the assessment made excluding concentrations of polybrominated diphenyl ethers (PBDEs) The overall area of interest used is based on the marine regions and subregions under the Marine Strategy Framework Directive. Additionally, Norwegian (Barent Sea and Norwegian Sea) and Icelandic waters (’Iceland Sea’) have been added (see Surrounding seas of Europe). Note that within the North East Atlantic region only the subregions within EEZ boundaries (~200 nm) have been included. This dataset underpins the findings and cartographic representations published in the report "Contaminants in Europe's Seas" (EEA, 2019): https://www.eea.europa.eu/publications/contaminants-in-europes-seas.
Coastal zones derived from Corine Land Cover classes 52x (raster 100m), Jun. 2012

[Lien vers la fiche source] Coastal zones are presented as a series of 10 consecutive buffers of 1km width each (towards inland). For this dataset, were treated as sea data all areas with class values of 52x (521: coastal lagoons, 522: estuaries, 523: sea and ocean) in Corine Land Cover (details in lineage).
Hydrographical pressure along European coastlines, Jan. 2020

[Lien vers la fiche source] This raster dataset presents the number of different hydrographical pressures per grid cell along the European coastlines. Hydrographical pressures are human activities that cause changes in hydrological conditions, i.e. changes to freshwater input, salinity, seawater flows, waves, currents, and temperature. Examples of such activities include riverine or coastal dams, offshore infrastructure, and outflows from power plants. The layer has been created using the Water Framework Directive (WFD) reported data on hydrographical pressures joined with the water body polygon features for the reference year 2016. The dataset was then rasterized into the EEA 10 km grid, and the cell values assigned with the number of different hydrographical pressures in the area covered by the cell. This dataset has been prepared for the calculation of the combined effect index, produced for the ETC/ICM Report 4/2019 "Multiple pressures and their combined effects in Europe's seas" available on: https://www.eionet.europa.eu/etcs/etc-icm/etc-icm-report-4-2019-multiple-pressures-and-their-combined-effects-in-europes-seas-1.
Review of 135 transformer datasheets from 3 manufacturers

[Lien vers la fiche source] This dataset results from the review of technical data of transformer for 135 datasheets from 3 manufacturers (Eaton, General Electric, Schneider). This dataset compiles characteristics, including mass, rated power, Transformer type, Primary and secondary voltage, number of phases, type of coil, losses, and efficiency. This research work was supported by the CDP PowerAlps, the project CIRCULAR, and EECONE, which received funding from the Chips Joint Undertaking under grant agreements 101112065 and BPI France.
EEA reference grid for France (10km), May 2013

[Lien vers la fiche source] The grid is based on proposal at the 1st European Workshop on Reference Grids in 2003 and later INSPIRE geographical grid systems. The sample grid available here is part of a set of three polygon grids in 1, 10 and 100 kilometres. The grids cover at least country borders and, where applicable, marine Exclusive Economic Zones v7.0, http://www.marineregions.org. Note that the extent of the grid into the marine area does not reflect the extent of the territorial waters.
Combined effects of land-based pressures on marine species and habitats in Europe's seas, Jun. 2020

[Lien vers la fiche source] The dataset presents the potential combined effects of land-based pressures on marine species and habitats estimated using the method for assessment of cumulative effects, for the entire suite of pressures and a selected set of marine species groups and habitats by an index (Halpern et al. 2008). The spatial assessment of combined effects of multiple pressures informs of the risks of human activities on the marine ecosystem health. The methodology builds on the spatial layers of pressures and ecosystem components and on an estimate of ecosystem sensitivity through an expert questionnaire. The raster dataset consists of a division of the Europe's seas in 10km and 100 km grid cells, which values represents the combined effects index values for pressures caused by land-based human activities. The relative values indicate areas where the pressures potentially affect the marine ecosystem. This dataset underpins the findings and cartographic representations published in the report "Marine Messages" (EEA, 2020).
Lacoast - Land cover change in coastal areas 1975-1990

[Lien vers la fiche source] LaCoast is a research project undertaken in the mid 1990 under the lead of the Joint Research Centre (JRC) and aimed at quantifying the changes of land cover types in a 10 km land strip from the coastline. LaCoast uses CORINE Land Cover version 1990 as its reference dataset and track differences of land cover changes using LANDSAT satellite images from the mid-1970's.
Assessment of contamination status using CHASE+ excluding mercury (Hg), Mar. 2019

[Lien vers la fiche source] This dataset presents the resulting assessment grid (based on the EEA reference grid) with the classification of chemical status of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD). This classification has been performed using the CHASE+ tool, with classifications of the matrices ‘water’, ‘sediment’ and ‘biota’ and indicators of ‘biological effects’, as well as an integrated classification of chemical status, combining results of all matrices. The chemical status is evaluated in five classes, where NPAhigh and NPAgood are recognised as ‘non-problem areas’ and PAmoderate, PApoor and PAbad are recognised as ‘problem areas’. This is the assessment made excluding concentrations of mercury (Hg). The overall area of interest used is based on the marine regions and subregions under the Marine Strategy Framework Directive. Additionally, Norwegian (Barent Sea and Norwegian Sea) and Icelandic waters (’Iceland Sea’) have been added (see Surrounding seas of Europe). Note that within the North East Atlantic region only the subregions within EEZ boundaries (~200 nm) have been included. This dataset underpins the findings and cartographic representations published in the report "Contaminants in Europe's Seas" (EEA, 2019).
Assessment of contamination status using CHASE+, Mar. 2019

[Lien vers la fiche source] This dataset presents the resulting assessment grid (based on the EEA reference grid) with the classification of chemical status of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD). This classification has been performed using the CHASE+ tool, with classifications of the matrices ‘water’, ‘sediment’ and ‘biota’ and indicators of ‘biological effects’, as well as an integrated classification of chemical status, combining results of all matrices. The chemical status is evaluated in five classes, where NPAhigh and NPAgood are recognised as ‘non-problem areas’ and PAmoderate, PApoor and PAbad are recognised as ‘problem areas’. The overall area of interest used is based on the marine regions and subregions under the Marine Strategy Framework Directive. Additionally, Norwegian (Barent Sea and Norwegian Sea) and Icelandic waters (’Iceland Sea’) have been added (see Surrounding seas of Europe). Note that within the North East Atlantic region only the subregions within EEZ boundaries (~200 nm) have been included. This dataset underpins the findings and cartographic representations published in the report "Contaminants in Europe's Seas" (EEA, 2019): https://www.eea.europa.eu/publications/contaminants-in-europes-seas.
Review of 186 photovoltaic inverter datasheets from 12 manufacturers

[Lien vers la fiche source] This dataset results from the review of technical data of photovoltaic (PV) inverters for 186 datasheets from 12 manufacturers (Huawei, Fronius, Schneider, Sungrow, TMEIC, Hoymiles, Mastervolt, Mitsubishi Electric, Siemens, Growatt, APsystems, SMA). This dataset compiles characteristics, including mass, rated output power, European efficiency, minimum and maximum input voltage, night time power consumption, volume, and number of phases. This research work was supported by the CDP PowerAlps, the project CIRCULAR, and EECONE, which received funding from the Chips Joint Undertaking under grant agreements 101112065 and BPI France.
Assessment of contaminant status of indicators of biological effects using CHASE+, Dec. 2019

[Lien vers la fiche source] This data set presents the resulting assessment grid (based on the EEA reference grid) with the classification of chemical status of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD), providing a mapping of contamination 'problem areas' and 'non-problem areas' based on measurements of biological effects. This classification has been performed using the CHASE+ tool, with classifications of the of contaminant status of indicators of biological effects. The status is evaluated in five classes, where NPAhigh and NPAgood are recognised as ‘non-problem areas’ and PAmoderate, PApoor and PAbad are recognised as ‘problem areas’. Monitoring biological effects is restricted to a few indicators (e.g. imposex) and data coverage is currently limited. Biological effects have thus been addressed in only 134 assessment units, mostly in the Baltic Sea, the North Sea and the North-East Atlantic Ocean. This data set underpins the findings and cartographic representations published in the EEA report “Contaminants in Europe’s seas” (No 25/2018). See the mentioned report for further information.
EUNIS Littoral biogenic habitat types (salt marshes), predicted distribution of habitat suitability - version 1, Nov. 2021

[Lien vers la fiche source] This metadata corresponds to the EUNIS Littoral biogenic habitat (salt marshes) types, predicted distribution of habitat suitability dataset. Littoral habitats are those formed by animals such as worms and mussels or plants (salt marshes). The verified littoral biogenic habitat samples used are derived from the Braun-Blanquet database (http://www.sci.muni.cz/botany/vegsci/braun_blanquet.php?lang=en) which is a centralised database of vegetation plots and comprises copies of national and regional databases using a unified taxonomic reference database. The geographic extent of the distribution data are all European countries except Armenia and Azerbaijan. The modelled suitability for EUNIS saltmarsh habitat types is an indication of where conditions are favourable for the habitat type based on sample plot data (Braun-Blanquet database) and the Maxent software package. The modelled suitability map may be used as a proxy for the geographical distribution of the habitat type. However, note that it is not representing the actual distribution of the habitat type. As predictors for the suitabilty modelling not only Climate and Soil parameters have been taken into account, but also so-called RS-EVB's, Remote Sensing-enabled Essential Biodiversity Variables like Landuse, Vegetation height, Phenology, LAI(Leave Area Index) and Population density. Because the EBV's are restricted by the extent of the Remote Sensing data (EEA38 countries and the United Kingdom) the modelling result does also not go beyond this boundary. The dataset is provided both in Geodatabase and Geopackage formats. The Training map files show the modelled suitable distribution, omitting the 10% of occurrence records in the least suitable environment under the assumption that they are not representative of the overall suitable habitat distribution. The 10 percentile training presence is an arbitrary threshold which omits all regions with habitat suitability lower than the suitability values for the lowest 10% of occurrence records.
Assessment of contamination status using CHASE+ excluding metals, Mar. 2019

[Lien vers la fiche source] This dataset presents the resulting assessment grid (based on the EEA reference grid) with the classification of chemical status of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD). This classification has been performed using the CHASE+ tool, with classifications of the matrices ‘water’, ‘sediment’ and ‘biota’ and indicators of ‘biological effects’, as well as an integrated classification of chemical status, combining results of all matrices. The chemical status is evaluated in five classes, where NPAhigh and NPAgood are recognised as ‘non-problem areas’ and PAmoderate, PApoor and PAbad are recognised as ‘problem areas’. This is the assessment made excluding concentrations of metals. The overall area of interest used is based on the marine regions and subregions under the Marine Strategy Framework Directive. Additionally, Norwegian (Barent Sea and Norwegian Sea) and Icelandic waters (’Iceland Sea’) have been added (see Surrounding seas of Europe). Note that within the North East Atlantic region only the subregions within EEZ boundaries (~200 nm) have been included. This dataset underpins the findings and cartographic representations published in the report "Contaminants in Europe's Seas" (EEA, 2019).
Europe Seas habitats potentially affected by anchoring, Jun. 2020

[Lien vers la fiche source] This vector dataset represents the benthic broad habitat types in Europe seas potentially affected by anchoring. The anchoring of vessels can produce damages to the seafloor and the loss of the habitat where it happens. It takes place in shallow waters, close to ports, where vessels have to wait for a spot in the port so they can load or offload (since ports have a limited amount of dockage). The anchoring areas allow vessels to safely anchor in protection from bad weather or other circumstances. The type of alterations to the habitats resulting from anchoring depend mainly on the dimensions and type of the anchor, as well as its movement resulting from the movement of the vessel due to currents or waves, which can increase the adverse effects. The dataset has been prepared in the context of the development of the first European Maritime Transport Environmental Report (to be published as an EMSA-EEA report in 2021).