AndreaBozzo/ceres-open-data-index huggingface dataset:
Bathymetry of the lagoon and hoa of Reao, Tuamotu Archipelago

[Lien vers la fiche source] Bathymetric data were acquired in Reao Atoll, a semi-enclosed atoll lagoon without reef pass but connected to ocean through numerous shallow spillways (known locally as "hoa") along its southern rim. This data was acquired as part of the GAIA (ManaGement strAtegy evaluatIon for small-scale fisheries in Atoll lagoons) project, which evaluates the sustainability of giant clam exploitation within the context of climate change. The lagoon of Reao is composed of three basins with varying depths (the NW basin being the shallowest and the SE basin the deepest). Bathymetric data were acquired from 29/04/2022 to 04/05/2022, within the lagoon with a Multibeam echo sounder IWBMS (NORBIT), and resampled at 5 m spatial resolution. Satellite-derived-bathymetry (SDB) at 10 m spatial resolution was established by coupling this bathymetric data with a Sentinel-2B image captured on 26/09/2020 and using the « Iterative Multi Band Ratio » technique (detailed methodology is described in Quéré et al. 2025). Finally, bathymetric surveys were carried out to characterize the nine most functional hoa of the atoll. One bathymetric survey was carried out in the longitudinal section of each hoa, while one or two surveys were carried out in their cross-sections.
CGFS Catch Data : Data from the Eastern English Channel Ground Fish Survey

[Lien vers la fiche source] The CGFS campaign is part of a historical series of fishing surveys that began in 1988 (CGFS Eastern part, conducted on the R/V Gwen Drez) and was extended to cover the entire English Channel regularly from 2018 (on R/V Thalassa). OInly data for the Eastern Channel is presented. For data from the Western Channel please see "WCGFS". For both surveys, the main objective is to collect basic data for estimating the state of resources through direct assessment of stock abundance and distribution, along with biological sampling of the catches. Taking place every year between mid-September and mid-October, it contributes to the European project for the contractualization of basic fishery data collection (DCF). The campaign also allows for sampling and a better understanding of the entire ecosystem, aligning with the implementation of an ecosystem-based approach to fisheries at the community level. The CGFS also provides data for numerous national and international research projects. The collected and validated data are transmitted at the end of each campaign to national databases (SIH, Harmonie, Coriolis) and the European database (DATRAS), enabling their use by different working groups and ensuring public access to this data. Finally, the CGFS data contributes to the baseline assessment of the impact of numerous marine aggregates extraction projects (through a multi-year convention signed between the Ministry of Ecology, Sustainable Development and Spatial Planning, IFREMER, and BRGM) planned or underway in the Eastern English Channel.
Image-based ecological assessment of deep-sea sponge, coral and other cnidarian assemblages through a morpho-functional approach : dataset and script repository

[Lien vers la fiche source] This DOI includes datasets compiling: matrices on megabenthos density, density of morpho-functional groups of sponges and cnidarians, environmental variables (per 200 m² sampling unit), and on the presence/absence of morphological traits for sponges and cnidarians; as well as supplementary information related to the publication ‘Image-based ecological assessment of deep-sea sponge, coral and other cnidarian assemblages through a morpho-functional approach’ (in preparation). The data were collected as part of the PAMELA project (Bourillet et al., 2013) during the PAMELA MOZ01 (Olu, 2014) cruises aboard the R/V L'Atalante, and PAMELA MOZ04 (Jouet & Deville, 2015) aboard the R/V Le Pourquoi Pas ?, enabling the exploration of four seamounts (Glorieuses and Sakalaves, Jaguar and Hall Banks platforms) and the Bassas da India Island slope terrace. Data were also collected on three outer slopes (east, north and west) of the island of Mayotte during the BIOMAGLO cruise(Corbari et al., 2017) aboard the R/V L'Antea. The images were captured from towed camera transects (SCAMPI, French IFREMER fleet). The megabenthic community dataset comprised 99 taxa of varying taxonomic resolution, identified from 9,614 images using the online image annotation platform BIIGLE 2.0 (Langenkämper et al., 2017). Details of the method used to identify and classify megafauna in the images are described in Hanafi-Portier et al. (2021), and those of the selection and curation of the final megabenthic community database in Hanafi-Portier et al. (2024). Details of the methodology used to produce the density matrices of morpho-functional groups of sponges and cnidarians are available in the Materials and Methods section of the publication ‘Image-based ecological assessment of deep-sea sponge, coral and other cnidarian assemblages through a morphofunctional approach’ (in preparation). Details on the methodology used to produce the environmental dataset are available in the Materials and Methods section of Hanafi-Portier et al. (2024). The datasets were used to assess the benefit of the morpho-functional characterisation in the assessment of (1) sponges and cnidarians diversity and spatial patterns at multiscales, (2) the environmental drivers shaping these morphological spatial structure, and (3) their potential structuring roles on the associated megafaunal communities overall.
Data associated to the long-term exposure of oysters and mussels to future ocean acidification and warming  in the Mediterranean Thau lagoon

[Lien vers la fiche source] Data associated to the long-term exposure of oysters and mussels to future ocean acidification and warming in the Mediterranean Thau lagoon. Data are survival, biometry, reproduction, and energy reserves of oysters and mussels collected during 14 months under ambient condition and warming and acidification expected for 2050, 2075 and 2100 based on the most likely CO2 emission scenario (SSP3-7.0, IPCC, 2023).
Past trajectory of a Northwest Europe socio-ecosystem at the land-sea interface: Case study of the northern watersheds of the Bay of Brest over the last 150 years

[Lien vers la fiche source] The Bay of Brest (BB) is a macro-tidal estuarine environment that has been exposed to strong anthropogenic pressures over the past few decades, especially after the Second World War. This makes the BB an ideal site for studying coastal ecosystem transformations since the Industrial Revolution. We analysed 5 sediment cores collected in 2 key BB areas with varying exposure to marine hydrodynamic processes: i) Elorn sector (3 cores) and ii) Bay of Daoulas (2 cores) in the inner BB, close to the mouth of the Daoulas river. Our study used palynological (pollen and dinoflagellate cysts) and benthic foraminiferal assemblages, sedimentological data, and elemental geochemistry, at a very fine temporal resolution (Daoulas core: 2-year resolution; Other cores: 2 to 16-year resolution). Working at a local spatial scale (i.e. BB) reveals robust correlations between the different driving forces and environmental changes at a high temporal resolution (i.e. sub-decadal) over the last 150 years. Our statistical analyses of these paleoecological time series reveal major breakpoints, specifically 4 key threshold periods: 1925–1938, 1960–1967, 1980–1987, and 2005, which are essential for understanding temporal changes in protist communities and BB landscapes through time. By combining these findings with a reanalysis of regional precipitation patterns (modelling approaches using meteorological reanalyses), nutrient concentration data, and historical accounts of land-use practices and industrial/mining/Second World War activities, we can identify the main drivers of coastal ecosystem transformations. Our findings emphasize the strong influence of agricultural practices on trophic changes and water quality decline in the BB, with coastal observatory series showing a notable increase in toxic algal blooms since the 1980s.
Lengths of Roads Inside the Cities by Type of the Road

This dataset contains Saudi Arabia Road Lengths by type and region for 2017 - 2018. Data from General Authority for Statistics . Export API data for more datasets to advance energy economics research. * We have used year converter to find the Gregorian year. Note: value for the columns Number of streetlights(Electrical Power) and Number of streetlights(Solar Energy) in 2019 are null and under process.
Hours Flown by Saudi Owned Aircrafts. by Month and Type of Aircraft

─────────────────────────────────────────────── * Source : Saudi Arabian Airlines Organization. ─────────────────────────────────────────────── This dataset contains Saudi Airlines-Hours Flown by owned Aircrafts by Month and type of Aircraft for 2008-2013 . Data from General Authority for Statistics. Follow datasource.kapsarc.org for timely data to advance energy economics research.
Transmission Generation Heat Map (SPEN_017) Data Quality Checks

This data table provides the detailed data quality assessment scores for the Transmission Generation Heat Map. The quality assessment was carried out on the 31st of January 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, at a minimum, bi-annual assessments of our data quality - for datasets that are refreshed more frequently than this, please note that the quality assessment may be based on an earlier version of the dataset. 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 dataset 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.
Linéaire de haies en Pays de la Loire

Ce jeu de données est calculé à partir du Référentiel Régional des Haies produit par l'IGN et publié par la Région Pays de la Loire. Le linéaire de haies est décliné en haies valides suivant la définition de l'IGN et en haies hors spécification IGN. En l'état, ce jeu de données ne permet pas un suivi dans le temps du linéaire de haies en Pays de la Loire. C'est pour cela qu'un seul millésime est diffusé. Pour en savoir plus sur la méthodologie de calcul de cet indicateur, nous vous invitons à consulter [cette fiche méthodologique produite par TEO]. Pour en savoir plus sur la définition d'une haie (dont distinction haies valides/non valides) et la méthodologie de construction de ce jeu de données, nous vous invitons à consulter la [page dédiée sur le site de TEO].
Supporting data for "Use of 3-nitrooxypropanol in early lactation dairy cows fed a high forage total mixed ration: Effect on enteric methane emissions, performance, and milk carbon isotopic signature"

[Lien vers la fiche source] The objective of this study was to determine the effect of the antimethanogenic compound 3-nitrooxypropanol on emissions, animal performance, milk composition and rumen fermentation in early lactating dairy cows fed a forage-rich diet. The 13C isotopic signature of milk as a potential proxy for methane emission status was also evaluated.
IRC lexicon for FNSSA - International Research Consortium lexicon for Food and Nutrition Security and Sustainable Agriculture

[Lien vers la fiche source] The Consortium Europe-Africa on Research and Innovation for Food Systems Transformation (CEA-FIRST) is a bicontinental effort put together to operationalise the International Research Consortium (IRC) as a long-term platform on Food and Nutrition Security and Sustainable Agriculture (FNSSA). One of the objectives of Work Package 2 of this project is to consolidate the existing FNSSA knowledge management system (KMS) tools to facilitate public access and knowledge sharing on relevant research activities and results. In this context, we have built the IRC lexicon to be integrated into the IRC knowledge management platform to fulfil semantic analysis and indexing needs. IRC lexicon aims to encompass the relevant themes in relation to the FNSSA roadmap. The lexicon is the combination of 4 existing semantic resources, i.e. inputs to construct the final lexicon: 1. The FNSSA database keywords, corresponding to the keywords used by SLU librarians to tag the documents’ topics 2. The LEAP4FNSSA lexicon, built during the first stage of the project ([https://www.sciencedirect.com/science/article/pii/S235234092200885X]) 3. KEOPS lexicon, built to address specific thematic in side-projects (climate change, food security) 4. ASSET lexicon, dealing with agroecology ([https://dataverse.cirad.fr/dataset.xhtml?persistentId=doi:10.18167/DVN1/TVN3AC]) These lexicons were merged and organized through several iterative steps involving two librarians (AL and AO), two researchers in text-mining (MR and SV) and a specialist in Information Management and KMS tools (TH). AL and AO validated the final version, ensuring that all keywords were categorized into their proper concept. The IRC lexicon is divided into 25 concepts containing a total of 1779 keywords, including 17 priority concepts (priority themes in the roadmap) : 1. Agricultural intensification: 75 keywords 2. Agroecology: 129 keywords 3. By-products: 33 keywords 4. Crops: 134 keywords 5. Economy: 65 keywords 6. Food product: 29 keywords 7. Food security: 33 keywords 8. Food value chains and market: 113 keywords 9. Innovation: 68 keywords 10. Land use: 60 keywords 11. Livestock and animal production: 52 keywords 12. Nutrition: 60 keywords 13. Plant and soil health: 106 keywords 14. Research and knowledge sharing: 79 keywords 15. Types of agriculture: 53 keywords 16. Water management: 85 keywords 17. Weather conditions: 41 keywords 1. Climate change: 78 keywords 2. Climate science: 51 keywords 3. Crisis: 105 keywords 4. Energy: 21 keywords 5. General: 73 keywords 6. Infrastructure: 13 keywords 7. One Health: 110 keywords 8. Social and cultural: 113 keywords
Ouvrages hydrauliques prioritaires dans le SAGE Estuaire de la Loire

Les ouvrages hydrauliques peuvent avoir un impact fort sur la continuité écologique. Notion introduite en 2000 par la directive cadre sur l’eau, la continuité écologique d’un cours d’eau est définie comme la libre circulation des organismes vivants et leur accès aux zones indispensables à leur reproduction, leur croissance, leur alimentation ou leur abri, le bon déroulement du transport naturel des sédiments ainsi que le bon fonctionnement des réservoirs biologiques (connexions, notamment latérales, et conditions hydrologiques favorables). Le SAGE* Estuaire de la Loire identifie les ouvrages les plus impactants comme prioritaires pour la restauration de la continuité écologique. Les solutions sont à proposer au cas par cas (arasement, effacement, aménagement, gestion des ouvertures) dans le cadre d’une concertation étroite avec les propriétaires et les gestionnaires d’ouvrage, en intégrant les objectifs des taux d'étagement et de fractionnement du SAGE et les objectifs d’accessibilité par l’anguille dans les secteurs de marais. Les maîtres d’ouvrage privilégient l’effacement ou la déconnexion des ouvrages quand ces solutions sont possibles. * Le schéma d’aménagement et de gestion de l’eau (SAGE) est un outil de planification, institué par la loi sur l'eau de 1992, visant la gestion équilibrée et durable de la ressource en eau.
EtudELEC Data, aggregated electricity consumption data from 400+ residential customers in France

[Lien vers la fiche source] This is grouped and aggregated electricity consumption data from the EtudELEC study conducted by the Observatoire du Transition Energétique Grenoble ([OTE-UGA]). If you find this dataset useful and like different groupings to be published or have any questions, please feel free to comment on the discussion dedicated to this dataset on the [OTE forum ]. The EtudELEC study only studies electricity consumption from residential dwellings around France. The study involved over 400 homes (individual houses and apartments) and spanned ~11 months from 25th October 2022 to 1st October 2023. The data is collected from the smart meter data (Linky data) which is only available with a time-step of 30 minutes. The data is in average watts consumed in a half-hour period. For reasons for privacy in line with GDPR laws, personal data such as individual home consumption will be shared as aggregated datasets as opposed to individual data points. The data from the participants were aggregated based on the following groupings: - Type of heating used and type of residence (stand-alone house vs apartment) This dataset is best viewed in the "Tree" view below. A folder is created for each of the groupings and sub-folders exist for all the subsequent groups. Each group folder contains: - a table of the minimum, mean, and maximum of the average power consumed for each 30-minute period (W), and - a JSON file with aggregated demographics information (number of inhabitants in different age backets, socio-professional category, year of construction etc.) of the group The datasets will be updated on a yearly basis following the renewal of consent of the panel members.
Structural annotation of five nuclear Brassica genomes

[Lien vers la fiche source] Structural annotations (.gff, mRNA and protein fasta files) of the nuclear genomes of five B. rapa and B. oleracea accessions: Two B. rapa (B. rapa ssp. narinosa cv. Wutacai and B. rapa ssp. trilocularis cv. R500) Three B. oleracea accessions (B. oleracea ssp. acephala cv C102, B. oleracea ssp. botrytis cv Nd125, a wild type B. oleracea ‘Bos01’ individual from Le Hode). Their corresponding genomes are available on ENA (https://www.ebi.ac.uk/ena/browser/view/PRJEB91446)
Structural annotation of five Brassica chloroplast genomes

[Lien vers la fiche source] Structural annotations (.gff) of the chloroplast genomes of five B. rapa and B. oleracea accessions: Two B. rapa (B. rapa ssp. narinosa cv. Wutacai and B. rapa ssp. trilocularis cv. R500) Three B. oleracea accessions (B. oleracea ssp. acephala cv C102, B. oleracea ssp. botrytis cv Nd125, a wild type B. oleracea ‘Bos01’ individual from Le Hode) Their corresponding genomes are available on ENA (https://www.ebi.ac.uk/ena/browser/view/PRJEB91446)
Indicateurs des séries annuelles issus des projections hydrologiques Explore2 pour le modèle SMASH sous RCP 8.5

[Lien vers la fiche source] Indicateurs des séries annuelles issus des débits journaliers simulés par le modèle hydrologique SMASH pour l'ensemble des projections climatiques Explore2 sous RCP 8.5. Ces fichiers résultent de l'agrégation temporelle des simulations hydrologiques sous runs historiques (avant 2005) et des projections hydrologiques (post 2005), fichiers NetCDF disponibles au téléchargement dans la collection [Explore2 - Projections hydrologiques]. Ce dépôt regroupe un tableau par indicateur et chaîne de simulation, c'est-à-dire, scénario d'émission RCP, couple GCM/RCM, correction de biais BC et modèle hydrologique HM. Ces données sont brutes et contiennent donc des chaînes de projections jugées aberrantes / horsains qu'il est possible de filtrer grâce à des [métadonnées supplémentaires]. Pour des raisons techniques, ces indicateurs sont regroupés par dossiers compressés selon les différentes phases du régime hydrologique. La description des chaines de modélisation du climat et celle des modèles hydrologiques sont, respectivement, disponibles dans le rapport [https://doi.org/10.57745/PUR7ML] et dans les annexes du rapport [https://doi.org/10.57745/S6PQXD]. Retrouvez le diagnostic des modèles hydrologiques résumé à l'échelle des régions hydrologiques dans les fiches téléchargeables ici : [https://doi.org/10.57745/DMFUXW]. Métadonnées supplémentaires : * Récapitulatif de l'ensemble des indicateurs hydrologiques : [https://doi.org/10.57745/JVNHQL] * Récapitulatif de l'ensemble des chaînes de simulation : [https://doi.org/10.57745/R6HG5X] * Description de l'ensemble des points de simulation : [https://doi.org/10.57745/UTKWR5] * Liste des chaînes de modélisation jugées aberrantes / horsains : [https://doi.org/10.57745/YZNENQ] * Récapitulatif des années pivots utilisées pour la TRACC : [https://doi.org/10.57745/DCOQM6] Décomposition des chaînes de caractères formant le nom des fichiers parquet, séparées par des "_" : {1} Indicateur : Le nom de l’indicateur, du type de statistique calculée {2} Échantillonnage : Échantillonnage temporel sur laquelle est calculé l’indicateur → {1}_{2} Variable : Variable résultante d'un indicateur temporellement contextualisé {3} EXP : Identifiant de l’expérience historique (post 2005) ou future (post 2005) {4} GCM : Identifiant du GCM forçeur {5} RCM : Identifiant du RCM {6} BC : Identifiant de la méthode de correction de biais statistique {7} HM : Identifiant du modèle hydrologique Les colonnes des fichiers parquet sont : * EXP : Voir ci-dessus * GCM : Voir ci-dessus * RCM : Voir ci-dessus * BC : Voir ci-dessus * HM : Voir ci-dessus * code : Code à 10 caractères du point de simulation fourni dans la [description des points de simulation] * date : Date du début de la période annuelle d'agrégation (i.e. 2042-05-01 indique que l'année hydrologique commence en mai, plus d'information dans les métadonnées de variable) * *Variable* : Voir ci-dessus Retrouvez des [scripts d'aide] pour utiliser ces données parquet.
Supplementary data for Falentin et al. 2025: Tables containing Resistance Gene Analogs (RGA) identified in Brassica rapa and B. oleracea genomes

[Lien vers la fiche source] Text file containing the gene names of the Resistance Gene Analogs identified in all genome assemblies generated in this study and those used for comparison (Table S01), the RGA genes that were unique to our newly assembled genotypes compared to others from the same morphotype (B. oleracea cv. C102: table S03; B. oleracea cv. ND124: table S05; B. oleracea ‘Bos01’: table S07) or from previous genome assemblies (B. rapa cv. R500: table S9; B. rapa cv Wutacai: tables S11). The orthologous relationships of Resistance Gene Analogs between our newly assembled genotypes and those from the same morphotype or from the previously assembled genome are also given (B. oleracea cv. C102: table S02; B. oleracea cv. ND124: table S04; B. oleracea ‘Bos01’: table S06; B. rapa cv. R500: table S08; B. rapa cv Wutacai: tables S10).