AndreaBozzo/ceres-open-data-index huggingface dataset:
Base de Données Géographique des Sols de France à 1/1 000 000 version 3.2.8.0, 10/09/1998

[Lien vers la fiche source] The Soil Geographical Data Base of France at Scale 1:1,000,000 is part of the European Soil Geographical Data Base of Europe. It is the resulting product of a collaborative project involving all the European Union and neighbouring countries. It is a simplified representation of the diversity and spatial variability of the soil coverage for France. The methodology used to differentiate and name the main soil types is based on the terminology of the F.A.O. legend for the Soil Map of the World at Scale 1:5,000,000. This terminology has been refined and adapted to take account of the specificities of the landscapes in Europe. It is itself founded on the distinction of the main pedogenetic processes leading to soil differentiation. The database contains a list of Soil Typological Units (STU). Besides the soil names they represent, these units are described by variables (attributes) specifying the nature and properties of the soils: for example the texture, the water regime, etc. The geographical representation was chosen at a scale corresponding to the 1:1,000,000. At this scale, it is not feasible to delineate the STUs. Therefore they are grouped into Soil Mapping Units (SMU) to form soil associations and to illustrate the functioning of pedological systems within the landscapes. Harmonisation of the soil data from the member countries is based on a dictionary giving the definition for each occurrence of the variables. Considering the scale, the precision of the variables is weak. Furthermore these variables were estimated over large areas by expert judgement rather than measured on local soil samples. This expertise results from synthesis and generalisation tasks of national or regional maps published at more detailed scales, for example 1:50,000 or 1:25,000 scales. Delineation of the Soil Mapping Units is also the result of expertise and experience. The spatial variability of soils is very important and is difficult to express at global levels of precision. Quality indices of the information (purity and confidence level) are included with the data in order to guide usage.
Baccalaureate success

Ce jeu de données présente, depuis 2019, les résultats au baccalauréat selon la voie, la spécialité de diplôme et le statut du candidat (scolaire, apprenti, individuel,…). Dans le cadre de la réforme du baccalauréat, les séries littéraire (L), économique et sociale (ES), et scientifique (S) disparaissent à compter de la session 2021. Abréviations utilisées : * ES : économique et sociale * L : littéraire * S : scientifique * STRH : sciences et technologies de l'hôtellerie et de la restauration * STI2D : sciences et technologies de l’industrie et du développement durable * STL : sciences et technologies de laboratoire * STMG : sciences et technologies du management et de la gestion * ST2S : sciences et technologies de la santé et du social * STD2A : sciences et technologies du design et des arts * Mention AB : assez bien * Mention B : bien * Mention TB : très bien
Municipal election results

Official result for each municipal election since 1996, including results for the Olympic plebiscite (2003) and City’s electoral system reform plebiscite (2004). ### Data Access This dataset has not yet been converted to a format compatible with our new platform. The data table provided contains links to access attributes information and election results data in CSV and XLS format. ### Dataset schema (Attributes) Links to pages describing the attributes are included in the data table. ### Data currency Before 4 p.m. on the fourth day following the close of General Voting, the Chief Election Officer must declare the official results of the election. This data set is a reflection of official results, and includes a breakdown of results by voting place. ### Data accuracy These are official and accurate results. Note: Some attribute names and calculation methods may change from election to election and are not directly comparable over time. Please consult corresponding attribute description for details. ### Websites for further information * [Anonymous ballot marking] dataset * [Voting Places datasets] * [Municipal elections] * [Vancouver Charter] * [Section 24: Non-resident property electors] * [Section 72: Mail ballot voting] * [City of Vancouver Election By-Law No. 9070] * Section 3.4-3.8 for special voting opportunities * Section 4 for mail ballot procedure
Dataset for "Measuring the presence and incidence of cholera in Hindustan: New data from primary sources for the colonial era"

[Lien vers la fiche source] New dataset covering 90 years of Cholera spreading in Hindustan from 1814 to 1904, issued from a collection of primary sources from medical reports and secondary sources. Harmonization procedure has been used to make these data comparable and corresponding to the current borders of India, Pakistan, Nepal, and Bangladesh.
Example schools in the municipalities in Västerbotten and the municipality of Örnsköldsvikerbo

Vill du ha information om skolor i kommunen kan du söka denna hos Skolverket Skolverketss öppna data innehåller en mängd information om skolor/utbildningsanordnare. Detta dataset innehåller information om skolor i Västerbottens kommuner samt i Örnsköldsvik kommun. Du finner information om Skolverkets öppna data här: [https://www.skolverket.se/om-oss/oppna-data] Datamängden i denna portal uppdateras (hämtas/skapas) inte regelbundet av denna portal. Vill du ha aktuella data hänvisar vi dig till Skolverket.
280_201201-HRDTM-Tyrrhenian Sea-60m

[Lien vers la fiche source] This Digital Terrain Model (DTM) is a high resolution bathymetry dataset that covers MEDOC survey. Multibeam data acquired in 2010 on board the R/V Sarmiento de Gamboa using an Atlas Hydrosweep DS-3 multi-beam echosounder.
280_201202-HRDTM-Balearic Sea-60m

[Lien vers la fiche source] This composite Digital Terrain Model (cDTM) is a high resolution bathymetry dataset that covers bathymetry surveys INDEMARES-2, ABIDES-2, ABIDES-3, ABIDES-ROV and ABIDES-5 . Multibeam data acquired in 2010, 2017 and 2018 on board the R/V Garcia del Cid using a Elac Seabeam 1050D echosounder and in 2017 on board the Sarmiento de Gamboa using an Atlas Hydrosweep DS-3 multi-beam echosounder.
280_201203-HRDTM-Atlantic_Gulf of Cadiz-60m

[Lien vers la fiche source] This composite Digital Terrain Model (cDTM) is a high resolution bathymetry dataset that covers bathymetry surveys INSIGHT_LEG1, FRAME-OBS, FRAME-MCS and INSIGHT_LEG2 . Multibeam data acquired in 2018 and 2019 on board the R/V Sarmiento de Gamboa using an Atlas Hydrosweep DS-3 multi-beam echosounder.
Circuits vélo pour le territoire de Cap Atlantique

Circuits vélo existants sur le territoire de Cap Atlantique (Assérac, Batz-sur-Mer, Camoël, Férel, Guérande, Herbignac, La Baule-Escoublac, La Turballe, Le Croisic, Le Pouliguen, Mesquer, Penestin, Piriac-sur-Mer, Saint-Lyphard, Saint-Molf).
Évolution et structure de la population (millésimé) - Roumois Seine

Ce jeu de données contient des informations sur l’évolution de la population de Roumois Seine pour chaque recensement depuis 2007 (2007, 2012, 2017). Les variables proposées par l’INSEE recouvrent des catégories démographiques liées à l’âge des individus, à leur sexe, à leur catégorie socio-professionnelle et à leur ancrage géographique.
Source code of program to manage flight mills with Raspberry Pi (2024)

[Lien vers la fiche source] We built flight mills to estimate flight capacities of insects. The dataset includes the source code of the program used to manage them with a Raspberry Pi single board computer (Version 1 to 3). The program detects signals arriving at the device's GPIOs and logs the corresponding data in text files. It was mainly developed in Crystal language (https://crystal-lang.org/) on a personal computer running Linux operating system, and cross-compiled on it.
Scripts to manage log files from URZF flight mills (2024)

[Lien vers la fiche source] We built flight mills to estimate flight capacities of insects and developed programs to manage them. During experiments, theses programs build specific data files (called log files). Basically, the log files are CSV-like files with a preamble and a postamble. The dataset includes scripts in Ruby and R languages to extract data from these log files, analyze them and produce usable R data files including summarized values. In conjunction to log files, the scripts are able to gathered local data and commands.
B-spline Dataset of "B-spline Curve Approximation With Transformer Neural Networks"

[Lien vers la fiche source] ### B-spline Dataset of B-spline Curve Approximation With Transformer Neural Networks article This dataset contains Cubic B-spline curves with randomly generated knots and control points. The set contains 160,000 different curves, each curve having between 9 and 16 knots, equally represented (20,000 per category). Curves are not sampled. This dataset was originally generated to train a Neural network on B-spline curve approximation. The dataset is divided in two subset : train and val of respectively 150,000 and 10,000 curves randomly sampled from the full dataset. You are free to use other subdivision of the dataset. More technical information about the data can be found in the Readme file. Feel free to contact the author if you have any questions/problems regarding the data.
Pretrained Transformers of "B-spline Curve Approximation With Transformer Neural Networks" article

[Lien vers la fiche source] ### Pretrained Transformers of B-spline Curve Approximation With Transformer Neural Networks article This dataset contains model checkpoints along with configuration and log files of trained transformer neural networks. Those networks have been trained following the methodology described in the link article. The following github repository can be used to read, test and process the data found in this dataset : [bspline-curve-approximation-transformer]. The Readme file can help you understand the nature of the data to help you in treating it yourself. A recent version of Pytorch is required to load some of the data (i.e. model checkpoints and parameters). The training logs and inference results come as csv and txt files and can be read and processed by any software of your choice. See Readme.md for a more detailed description of files and parameters. Feel free to contact the author regarding questions/problems with the data.
airGRdatassim: Ensemble-Based Data Assimilation in GR Hydrological Models. R package version 0.1.4

[Lien vers la fiche source] Add-on to the 'airGR' package which provides the tools to assimilate observed discharges in daily GR hydrological model. The package consists in two functions allowing to perform the assimilation of observed discharges via Ensemble Kalman filter or Particle filter.
airGR: Suite of GR Hydrological Models for Precipitation-Runoff Modelling. R package version 1.7.6

[Lien vers la fiche source] Hydrological modelling tools developed at INRAE-Antony (HYCAR Research Unit, France). The package includes several conceptual rainfall-runoff models (GR4H, GR5H, GR4J, GR5J, GR6J, GR2M, GR1A) that can be applied either on a lumped or semi-distributed way. A snow accumulation and melt model (CemaNeige) and the associated functions for the calibration and evaluation of models are also included. Use help(airGR) for package description and references.
Impact of a 2-month exercise training program on glycaemic fluctuations on days with and without exercise in adults with type 1 diabetes.

[Lien vers la fiche source] In type 1 diabetes (T1D), some few studies have explored the impact of training on glycaemic fluctuations. However, no research aimed to assess glycaemic excursions and their progression throughout a 2-month training program, distinguishing those observed around exercise sessions from those of non-exercising days. Nineteen (13 female) adults with T1D participated in 2-3 supervised exercise (aerobic/strength) 90-min weekly sessions over 2 months. Glycaemic excursions (continuous glucose monitoring) were calculated for specific periods (24-hour, nocturnal; periods before, during, after exercise sessions) and compared between day with and without an exercise session. Linear mixed models or binary/multinomial logistic regressions with random effects were used to assess the effect of weeks of training and type of day, including or not an exercise session, on glycaemic excursions. The data made available on data.gouv corresponds to all the data files used for these analyses. Access to the data can also be requested from Elsa Heyman. During the 2-month training, nights following exercise showed reduced risk of hyperglycaemic (>10.0mmol⋅L-1) compared to non-exercise nights. This difference attenuated with weeks of training, in parallel to a progressive increased risk of time >16.7mmol⋅L-1 during early and late recovery periods after exercise sessions. Overall, independently of exercise session occurrence, level 1 and 2 nocturnal hypoglycaemic risk increased as the training weeks passed. In conclusion, for patients with type 1 diabetes who engage in regular physical activity, it is crucial to be vigilant about post-exercise glycaemic excursions, particularly at night. Although acute exercise (i.e., day with vs. without a training session) reduced nocturnal hyperglycaemia without increasing the risk of hypoglycaemia, this risk of hypoglycaemia progressively increased after several weeks of training, during the nights, even those not subsequent to an acute exercise. Therefore, enhancing glycaemic control, especially at night, using continuous glucose monitoring systems is essential, not only during the first weeks of training, but also after several weeks.
Data from the paper entitled 'Glycaemic effects of a 156-km ultra-trail race in athletes: an observational field study'

[Lien vers la fiche source] Objectives We aimed to explore the impact of an ultra-endurance race on continuously measured glycaemia and to understand potential physiological mechanisms, as well as the consequences for performance and behavioural alertness. Methods Fifty-five athletes (78% men, 43.7 +/- 9.6 years) ran a 156-km ultra-trail race (‘Trail Scientifique de Clécy’: six 26-km laps, total elevation +6000 m). Participants wore a masked continuous glucose monitoring sensor from the day before the race until 10 days post-race. Blood was taken at rest, during refuelling stops after each lap, and after 24-h recovery. Running intensity (% heart rate reserve), performance (lap times), psychological stress and behavioural alertness were explored. Linear mixed models and logistic regressions were carried out. Results No higher risk of hypo or hyperglycaemia was observed during the exercise phases of the race (i.e., excluding stops for scientific measurements and refuelling) compared with resting values. Laps comprising a greater proportion of time spent at maximal aerobic intensity were nevertheless associated with more time >180 mg/dL (P=0.021). A major risk of hyperglycaemia appeared during the 48-h post-race period compared with pre-race (P<0.05), with 31.9% of the participants spending time >180 mg/dL during recovery vs. 5.5% during resting. Changes in circulating insulin, cortisol and free fatty acids followed profiles comparable with those usually observed during traditional aerobic exercise. However, creatine phosphokinase, and to a lesser extent lactate dehydrogenase, increased exponentially during the race (P<0.001) and remained high at 24-h post-race (P<0.001; respectively 43.6 and 1.8 times higher vs. resting). Glycaemic metrics did not influence physical performance nor behavioural alertness. Conclusion Ultra-endurance athletes were exposed to hyperglycaemia during the 48-h post-race period, possibly linked to muscle damage and inflammation. Strategies to mitigate muscle damage or subsequent inflammation before or after ultra-trail races could limit recovery hyperglycaemia and hence its related adverse health consequences.
Seasonal Physico-Chemical and High-Frequency Monitoring of Lake Tignes for Mecanistic Model Calibration and Climate Change Impact Assessment (2022-2023)

[Lien vers la fiche source] This dataset, collected by CARRTEL-INRAE in collaboration with the municipality of Tignes, is part of a study on climate change impacts on the thermal structure and water quality of Lake Tignes. Monthly physico-chemical measurements (temperature, conductivity, pH, salinity, oxygen concentration, and oxygen saturation) were conducted from May 2022 to March 2023 at the deepest points of the lake's two basins using a KorEXO multi-parameter probe. Additional high-frequency data on temperature, oxygen, and light were gathered at various depths near the outlet sub-basin from May 2022 to September 2023. Laboratory analyses focused on the chemical composition of the water in the euphotic and deeper layers (e.g., nutrients, ions, chlorophylls, and pigments) following standardized protocols. Phytoplankton community counts were also conducted. Lake tributary parameters were measured with a multiparameter probe. Detailed methodology and data descriptions are available in the scientific report: Prospective et effets du changement climatique sur le lac de Tignes (CARRTEL, 2024, ⟨hal-04722121⟩).
French3lakes - Freshwater zooplankton community composition data from French Peri-Alpine lakes

[Lien vers la fiche source] Dataset of zooplankton community composition and abundance, waterbody characteristics, physical, and chemical data from 3 French Peri-Alpine lakes (Geneva, Annecy, Bourget). Samples have been collected monthly and bimonthly in the top 50 m using a 200 µm plankton net and identified to the species level. The dataset is part of a large initiative, the Zooplankton International Geospatial (ZIG) dataset, which includes zooplankton data from 311 inland lakes and reservoirs. ZIG aims to provide a comprehensive data collection to explore the role of zooplankton as indicators of environmental change. Funding: OLA-IS (Alpine Lakes Observatory - https://si-ola.inrae.fr/si_lacs/login.jsf) - AnaEE-France, INRAE Thonon les Bains, CIPEL, SILA, CISALB This work was conducted as a part of the FreshH2O Zoops Working Group. The Working Group was supported by (1) the John Wesley Powell Center for Analysis and Synthesis, funded by the U.S. Geological Survey, (2) the French Foundation for Research on Biodiversity (FRB) through its synthesis center CESAB, and (3) the Environmental Data Science Innovation & Inclusion Lab (ESIIL), a NSF funded data synthesis center led by the University of Colorado Boulder in collaboration with NSF’s CyVerse at the University of Arizona and the University of Oslo (NSF Award Number DBI-2153040).
airGRteaching: Teaching Hydrological Modelling with the GR Rainfall-Runoff Models ('Shiny' Interface Included). R package version 0.3.5

[Lien vers la fiche source] Add-on package to the 'airGR' package that simplifies its use and is aimed at being used for teaching hydrology. The package provides 1) three functions that allow to complete very simply a hydrological modelling exercise 2) plotting functions to help students to explore observed data and to interpret the results of calibration and simulation of the GR ('Génie rural') models 3) a 'Shiny' graphical interface that allows for displaying the impact of model parameters on hydrographs and models internal variables.
Data from the paper entitled 'Barriers to physical activity in children and adults living with type 1 diabetes: a complex link with real-life glycemic excursions".

[Lien vers la fiche source] Summary of the methodology : Sixty-two adults, and 53 children/adolescents living with type 1 diabetes along with their parents, completed the BAPAD-1 questionnaire on barriers to PA. Continuous glucose monitoring data were collected during one week of everyday life for 26 adults and 33 children/adolescents. Multiple linear regressions were used to explore links between BAPAD-1 scores and glycemic excursions experienced during and after everyday life self-reported PA sessions, controlling for behavioral (accelerometry) and demographic confounders. For the full methodology, please refer to the paper.
Flux mensuels collectés et taux des Livret A, LDDS et LEP depuis 2024

L'épargne réglementée fait référence aux placements dont les conditions de fonctionnement, telles que les critères d'éligibilité, les plafonds de dépôts, les modalités de versement, les taux de rémunération et la fiscalité, sont définies par les pouvoirs publics, garantissant ainsi un rendement sécurisé. Tous les six mois, la Banque de France calcule et propose au ministère de l’Économie et des Finances les taux de rémunération pour les livrets d'épargne réglementée, comme le livret A et le livret d’épargne populaire. Ces taux sont déterminés par des formules de calcul réglementaires, mais peuvent être ajustés en cas de circonstances exceptionnelles. La Caisse des Dépôts et Consignations (CDC) joue un rôle central dans la gestion de l'épargne réglementée, en centralisant 60 % des encours du livret A et du LDDS, ainsi que la moitié des encours du LEP. Ainsi, elle fournit des données mensuelles sur les montants collectés (en milliards d'euros) depuis 2024 et les taux associés à ces livrets. Le livret A est un compte d’épargne rémunéré offrant une disponibilité immédiate des fonds. Il est proposé par tous les établissements bancaires. En revanche, le LEP est spécifiquement destiné aux personnes à revenus modestes. Pour plus d'informations, consulter la rubrique Presse de la CDC ([https://www.caissedesdepots.fr/presse]) et les rubriques du Service Public : * [https://www.service-public.fr/particuliers/vosdroits/F2365] * [https://www.service-public.fr/particuliers/vosdroits/F2368] * [https://www.service-public.fr/particuliers/vosdroits/F2367]
ArtSymbioCyc, a metabolic network database collection dedicated to insect symbioses

[Lien vers la fiche source] The ArtSymbioCyc database is a collection of genomic resources for insect hosts and their obligate symbiotic or commensal bacteria annotated with the CycADS information system. Dedicated to metabolism, ArtSymbioCyc uses the powerful tools of the BioCyc community to analyze, compare and model the metabolic networks of the symbiotic partners on a genome-wide scale (including pathways, reactions or metabolites). The [ArtSymbioCyc] database collection is a dedicated resource that provides tools to study and compare the adaptive metabolic capacities of symbiotic organisms and to identify specific targets that may destabilize symbiotic equilibria and be useful for pest control. Here we put the functional annotation data used to reconstruct the metabolic networks from the different databases, as well as the reactions and metabolic networks that were inferred.
Example Companies in Umea (Open data from Bolagsverket)

Vill du ha information om företag i kommunen kan du söka denna hos Bolagsverket. Bolagsverkets öppna data innehåller en mängd information om företag. Detta dataset innehåller information om företag där postnumret i adressen finns inom Umeå kommuns gränser. Det är inte säkert att verksamheten bedrivs i Umeå. På motsvarande sätt kan det finnas företag med adressen utanför Umeå kommun som bedriver verksamhet inom Umeå kommuns gränser. Du finner information om Bolagsverkets öppna data här: https://bolagsverket.se/apierochoppnadata.2531.html Detta är ett exempel på den data som kan hämtas. Denna datamängd uppdateras (hämtas) inte regelbundet av denna portal och kan därför vara missvisande. Vill du ha aktuella data hänvisar vi dig till Bolagsverket.