AndreaBozzo/ceres-open-data-index huggingface dataset:
Data for "Uncovering Hidden Sensitivity: Inter-Individual Growth Variation in Earthworms Under Fungicide Exposure"

[Lien vers la fiche source] Environmental risk assessments (ERAs) of chemicals typically rely on standardized ecotoxicological tests that overlook inter-individual variability, despite its importance in ecological resilience and evolutionary success. Contaminants can disrupt individual differences by altering life-history traits, amplifying fitness disparities, favoring certain phenotypes, and reducing genetic diversity, ultimately impacting population dynamics and adaptability. However, the extent to which pollutants influence inter-individual variability and its population-level consequences remains poorly understood. To address this, our study examines the inter-individual variability of growth trajectories in the earthworm Aporrectodea caliginosa in response to sublethal exposure to Swing® Gold fungicide. Using a longitudinal design with 30 exposed and 30 unexposed individuals, we compared mean and inter-individual growth rate variability. While the fungicide had a weak effect on the cohort’s mean growth rate, we observed a three-fold increase in inter-individual variability in the exposed group. This increase highlighted a subset of highly sensitive individuals, whose growth was reduced by up to 10% compared to the average response. Our results suggest that focusing solely on population mean effects could overlook impacts on sensitive individuals, who could serve as early indicators of environmental stress. Incorporating individual variability into ecotoxicological studies is challenging due to the labor-intensive nature of individual monitoring and the need for larger datasets. Nonetheless, these efforts are essential for refining higher-tier ERA frameworks, improving safety factors for intraspecies variability, and defining regulatory thresholds. A better understanding of how contaminants affect inter-individual variation will enhance the accuracy and ecological relevance of risk assessments, ultimately capturing the long-term implications for population and ecosystem dynamics.
MTBLS752: Untargeted food contaminant detection using UHPLC-HRMS combined with multivariate analysis: Feasibility study on tea (Dataset 1 - Development)

[Lien vers la fiche source] Powerful data pretreatment strategies inspired from the field of metabolomics were adapted to chemical food safety context to enable samples discrimination by multivariate methods based on low abundance ions. A highly automated workflow was produced. The open-source XCMS package was used and efficient data filtration strategies were set up. Data were treated using Independent Components Analysis, and data mining strategies developed to automatically detect and annotate ions of low abundance by coupling blind data exploration strategies with a broad scale database approach. Our method was efficient in discriminating tea samples based on their contamination levels (even at 10µg/kg) and detecting unexpected impurities in the spiking mix. Several “tracer” contaminants were considered, covering a broad range of physicochemical properties and structural diversity with overall 66% detected and annotated blindly. The methodology was successfully applied to a data set exhibiting only 3 “tracer” contaminants (at 50µg/kg) and more product diversity. Dataset 1 with 1 tea spiked with 32 contaminants and referred to as the Development dataset is reported in the current study MTBLS752. Dataset 2 with 2 teas spiked with 3 contaminants and referred to as the Validation dataset is reported in MTBLS754.
MTBLS771: Untargeted food chemical safety assessment: A proof-of-concept on two analytical platforms and contamination scenarios of tea (Green tea study)

[Lien vers la fiche source] This study aims at assessing the capability of comparing and combining different instrumental platforms in an untargeted approach with a view of detecting chemical contaminants in food matrices at low levels. A strategy based on liquid chromatography-high resolution mass spectrometry (LC-HRMS) and chemometrics has been applied on two different complex food contamination scenarios, with tea as study product. The first scenario aimed at mimic the presence of a dozen of contaminants at levels just above regulatory limits (i.e. 10 and 30 μg/kg); the second scenario, more complex, aimed at simulate the presence of several different contaminations at levels close to regulatory limits (10 μg/kg) in different samples. This work was carried on two LC-HRMS platforms (with respectively ToF and Orbitrap mass analyzer technologies), and a highly automated data treatment workflow was implemented to deal with data acquired on both platforms. The untargeted approach performed well on all scenarios (even the most complex) and analytical platforms. Performance comparison between LC-HRMS technologies was made possible thanks to a vendor-neutral data treatment process. Sub-samples of green tea (Bancha type, gross, Japan) were spiked at different levels with a pool of 11 contaminants and then extracted with a generic method and analyzed by LC-HRMS (in both positive and negative ionization modes) on two platforms (respectively Orbitrap and ToF to generate a total of four data sets. Green tea spiked with contaminants is reported in the current study MTBLS771. Black tea spiked with contaminants is reported in MTBLS772.
MTBLS10568: EFFECT OF DIFFERENT POOLED QC SAMPLES ON DATA QUALITY DURING AN INTER-BATCH EXPERIMENT IN UNTARGETED UHPLC-HRMS ANALYSIS ON TWO DIFFERENT MS PLATFORMS

[Lien vers la fiche source] Quality control (QC) samples are commonly used in metabolomics approaches for three main reasons: (i) the initial conditioning of the column; (ii) the correction of analytical drift especially between batches; and (iii) the evaluation of measurement precision. In practice there are several ways to prepare and conserve QC samples. The most common in untargeted metabolomics is to pool samples after or before extraction, in order to obtain pooled QC samples accounting respectively for analytical variance or for both analytical and sample preparation variances. In this study, focusing on untargeted analysis of tea (Camellia sinensis) leaves, we compared three ways of preparing pooled QC samples (two usual and one unusual QC sample preparations) and their efficiency to improve data quality in terms of inter-batch correction, measurement precision, and VIP candidates selection on datasets obtained using two mass spectrometry (MS) technologies (Orbitrap and time of flight (QToF)). We also investigated the effect of data processing modalities, based on the different QC preparations, on data loss and on the global structure of the datasets. Generally, our results show that usual QC sample preparation leads to comparable datasets quality in terms of precision and dispersion in both MS instruments. They also show that QC preparation is crucial for VIP selection, in fact, up to 54% of biomarkers candidates are specific of the QC preparation type used for data processing.
MTBLS12279: Untargeted LC-HRMS approaches combined with feature-based molecular networking to annotate reaction markers in processed foods

[Lien vers la fiche source] The rising consumption of ultra-processed foods (UPFs), linked to multiple health risks, underscores the need to characterise the chemical profile of formulated and processed goods to improve their quality and safety. This study aims to develop untargeted approaches based on LC-HRMS and LC-HRMS/MS, coupled with feature-based molecular networking (FBMN), to explore, for the first time, the chemical reactivity within a well-characterised UPF-like food matrix (sponge cake). Three controlled baking conditions were applied to the formulated cake to induce thermal reactivity and generate diverse chemical profiles. Principal component analysis and heatmap clustering of untargeted LC-HRMS data from cake extracts were able to effectively discriminate samples based on the thermal process intensity. Approximately 75% of the detected features were indeed involved in the reactivity. FBMN revealed different groups of compounds (including precursors and advanced products) associated with Maillard and caramelisation reactions, and helped annotation of several reaction markers. This is the first application of FBMN on widely consumed processed foods such as baked products, opening new perspectives for generating high-throughput untargeted data to annotate reaction markers from complex food matrices.
Connection Queue Information

Our Connection Queue Information dataset contains information from the connections reform process, giving the generator connections in the scope of the process, their GSP, Technology, Export Capacity, Queue Position and Transmission Gate. A queue position of 0 indicates no queue position. If you are unsure of any of the column meanings, please hover over the column heading for a description. Related Feature Pages [Major Projects Pipeline] – Our Major Projects Pipeline page provides a view of GSP status and connection queues. Glossary of Terms Our [Glossary] dataset provides definitions for various terms and acronyms found throughout our data. If the term you are searching for isn't in our list, please let us know via our [Open Data team] and we will get it added! Data Governance If you wish to view the data triage document for any dataset, they can be found in our [Data Triage Assessment] dataset. This dataset does NOT require a login to view Any data caveats for the dataset are listed below - None
Duplication des données : Carte d’occupation des sols du CES OSO – THEIA (2016-2023, France métropolitaine)

[Lien vers la fiche source] [Description officielle des données] [Portail officiel de téléchargement] En raison de la trouvabilité et de l’accessibilité technique limitées des données, ce dépôt regroupe l’ensemble des données raster de l’occupation du sol (OSO) téléchargeables sur la plateforme GEODES du CNES. Point sur les Licences Les données originales sont diffusées sous la licence [ODbL 1.0] selon le [gouvernement français]. Cependant, d'après cette même source, cette licence est compatible avec la licence « Etalab ». Ce point est d'ailleurs confirmé par la mention de l'utilisation de la licence Etalab sur le [site de Theia]. Ainsi, ces données sont redistribuées sous la Licence Ouverte ETALAB V2.0. API L'accès à une API de découpe selon un polygone des cartes d'occupation du sol est disponible sur demande. Proposition de citation > OSO – THEIA / CES OSO, Cartes annuelles d’occupation du sol (OSO, France métropolitaine), CNES/GEODES, niveau L3B-OSO. Licence : ODbL 1.0 / Licence Ouverte v2.0 (Etalab). Accès officiel : https://geodes-portal.cnes.fr. Redistribution (non officielle) : https://doi.org/10.57745/UZ2NJ7
Adresses de Rennes Métropole renseignées par divers zonages

Cette couche d'adresses est le résultat d'une intersection spatiale entre la couche des adresses du référentiel Voies et Adresses de Rennes Métropole (RVA) et divers zonages administratifs. L'adresse est présentée sous 2 formes : - adresse complete : 1 bis B rue du Botrel, Acigné - adresse éclatée en plusieurs champs : numero : 1 extension : bis batiment : B denomination_voie : Rue du Botrel commune_nom : Acigné Voici les zonages attribués à une adresse : - sous-quartiers (Rennes uniquement) => sousquartier_code / sousquartier_nom - quartiers (Rennes uniquement) => quartier_code / quartier_nom - quartiers prioritaires de la politique de la ville => quartierprioritaire_code / quartierprioritaire_nom - quartiers prioritaires élargis de la politique de la ville => quartierprioritaireelargi_nom - cantons => canton_code / canton_nom - circonscriptions législatives => circonscription_code / circonscription_nom - Iris Insee => iris_code / iris_nom - Conseil de quartier (Rennes uniquement) => nuconseil / nomconseil - Comité de secteurs Rennes Métropole => num_secteur / nom_secteur - Code postal => code_postal - Plateforme voirie => dve_plateforme
Swisslos-Fonds: Unterstützte Projekte nach Sparte und Betrag (seit 2011)

Durch den Kanton Basel-Landschaft geleistete Beiträge aus dem kantonalen Fonds der Genossenschaft der Interkantonalen Landeslotterie SWISSLOS an wohltätige, gemeinnützige und kulturelle Projekte seit 2011. Kriterien für unterstützte Projekte können der Verordnung über den Swisslos-Fonds ([SGS 543.12]) entnommen werden. Über den [Swisslos Sportfonds] des Kantons Basel-Landschaft geleistete Beiträge sind nicht Teil dieses Datensatzes.
Référentiel des communes du canton de Fribourg

Ce jeu de données répertorie l'ensemble des communes du canton de Fribourg, y compris les changements administratifs (création, dissolution), depuis 1848. Pour les communes et les districts, les données sont déclinées selon l'état historique à un moment donné ainsi que l'état actuel correspondant. La distance administrative représente le nombre d'opérations à effectuer pour atteindre l'état actuel (état actuel = 1). Les données manquantes (NA) concernent les cas non applicables, à savoir les fusions impliquant une commune d'un autre canton, ainsi que les lacs ou forêts fribourgeois comptés comme localités. Pour plus d'information sur le répertoire officiel des localités : [https://www.swisstopo.admin.ch/fr/repertoire-officiel-des-localites]
Data for "From past exceptional extremes to frequent future risks: How climate change shapes the fate of common wheat in France"

[Lien vers la fiche source] Dataset associated with the article "From past exceptional extremes to frequent future risks: How climate change shapes the fate of common wheat in France". This dataset documents the evolution, from 1975 to 2100, of the probabilities of exceeding a decennial event (the 90th percentile defined over the historical reference period 1975-2005). The data cover various ecoclimatic risk indicators for wheat (individual (n=32) and combined (n=9) and are broken down by: * Wheat ideotypes (Late–Late), * Two emission scenarios (RCP 2.6, RCP 8.5), * The four main eco-climatic zones for wheat production in France. This dataset also contains the cross-validation results for all the GAMLSS models used to compute exceedance probabilities.
Le aree verdi, piazze e vie di Bologna dedicate alle donne

In questa sezione sono pubblicati i dati in formato geojson relativi alla mappa dei toponimi femminili e alle biografie correlate. Inoltre vengono presentati i risultati di un lavoro, a cura del data team di Agenda Digitale, nel quale è stata analazzita la toponomastica femminile con tecniche alternative di datascience per un confronto con i risultati della ricerca del SIT. Il codice sorgente (in linguaggio python) verrà rilasciato a breve sul GitHub del Comune di Bologna. La mappa dei toponimi femminili è stata realizzata dal SIT (Sistemi informativi territoriali) del Comune di Bologna
e8319dba-0bf6-4d7b-8abd-0f5e36039f03

[Lien vers la fiche source] Bathymétrie au large du cap d'Antibes, en mer Ligure, au pas de 2 mètres. Ce jeu de données est un Modèle Numérique de Terrain bathymétrique, issu de l'acquisition acoustique du sondeur multifaisceau EM2040 de l'AUV Idefx, lors de la campagne d'essais ESSPOSIT-2022. Référence verticale : Niveau observé des mers Description de la campagne : ARNAUBEC Aurelien, BOUHIER Marie-Edith (2022) ESSPOSIT-2022 cruise, RV L'Europe, https://doi.org/10.17600/18002712
Verkehrszählung MIV Stadt St.Gallen (nach Fahrzeugkategorien SWISS10, 2019-2022)

Das Tiefbauamt der Stadt St.Gallen zählt den Motorisierten Individualverkehr (MIV) an verschiedenen Standorten der Stadt St.Gallen und ihrer Umgebung. Dieser Datensatz zeigt die Daten dieser Verkehrszählungen aufgeschlüsselt nach den unterschiedlichen Fahrzeugkategorien gemäss SWISS10. Datenstruktur: * ORT-ID: ID der Zählstelle * BEZEICHNUNG: Name/Ort der Zählstelle * DATUM * WOCHENTAG * RI: Richtungsnummer der Messung. Die Daten zeigen eine Zeile pro Richtungsnummer. * KLASSE: Fahrzeugkategorie nach SWISS10 mit entsprechendem NAME_D auf Deutsch und der Zuordnung zu den entsprechenden Kategorien nach SWISS7 und SWISS6 * 1 - 24: Uhrzeit (Stunde), wann die Anzahl Fahrzeuge gemessen wurde. Anmerkung: Durchgehende Nullen für eine spezifische Richtungsnummer bedeuten, dass diese Richtungsnummer für die entsprechende Zählstelle nicht gebraucht wird. * TAGESTOTAL: Anzahl gemessene Fahrzeuge pro Richtung (=Summe 1-24)
SPD LTDS Appendix 2 Transformer Data (Table 2)

The "SPD LTDS Appendix 2 Transformer Data (Table 2)" data table provides the equipment parameter data for each group of transformers on the SP Distribution (SPD) system. The insertion of N/K in the table indicates where a parameter has not been verified. The column titled "Reverse Rating" shows the reverse power flow capability of the tap changer. Click [here] to access our full Long Term Development Statements for both SP Distribution (SPD) & SP Manweb (SPM). The table gives the following information: 1. HV and LV connection node per substation 2. Positive sequence resistance and reactance per substation 3. Minimum and maximum tap percentage per substation 4. Continuous and reverse rating per substation For additional information on column definitions, please click on the Dataset schema link below. ### Disclaimer Whilst all reasonable care has been taken in the preparation of this data, SP Energy Networks does not accept any responsibility or liability for the accuracy or completeness of this data, and is not liable for any loss that may be attributed to the use of this data. For the avoidance of doubt, this data should not be used for safety critical purposes without the use of appropriate safety checks and services e.g. LineSearchBeforeUDig etc. Please raise any potential issues with the data which you have received via the feedback form available at the Feedback tab above (must be logged in to see this). ### Data Triage As part of our commitment to enhancing the transparency, and accessibility of the data we share, we publish the results of our Data Triage process. Our Data Triage documentation includes our Risk Assessments; detailing any controls we have implemented to prevent exposure of sensitive information. Click[here]to access the Data Triage documentation for the Long Term Development Statement dataset. To access our full suite of Data Triage documentation, visit [the SP Energy Networks Data & Information page]. [Download dataset metadata (JSON)]
SPD LTDS Appendix 6 Connection Activity (Table 6)

The "SPD LTDS Appendix 6 Connection Activity" data table provides an indication of areas of interest, or activity in the SP Distribution system from a connection perspective. The connection activity has been collated and displayed in Table 6, together with an indication of source substations. Click [here] to access our full Long Term Development Statements for both SP Distribution (SPD) & SP Manweb (SPM). The table gives the following information: 1. Interest in connections to the distribution system for both demand and generation connections 2. Indication of source substation (GSPs and Primary level) 3. Indications of feasibility work undertaken 4. Offer conversion data (acceptances versus offers) For additional information on column definitions, please click on the Dataset schema link below. ### Disclaimer Whilst all reasonable care has been taken in the preparation of this data, SP Energy Networks does not accept any responsibility or liability for the accuracy or completeness of this data, and is not liable for any loss that may be attributed to the use of this data. For the avoidance of doubt, this data should not be used for safety critical purposes without the use of appropriate safety checks and services e.g. LineSearchBeforeUDig etc. Please raise any potential issues with the data which you have received via the feedback form available at the Feedback tab above (must be logged in to see this). ### Data Triage As part of our commitment to enhancing the transparency, and accessibility of the data we share, we publish the results of our Data Triage process. Our Data Triage documentation includes our Risk Assessments; detailing any controls we have implemented to prevent exposure of sensitive information. Click [here]to access the Data Triage documentation for the Long Term Development Statement dataset. To access our full suite of Data Triage documentation, visit [the SP Energy Networks Data & Information page]. [Download dataset metadata (JSON)]
Grid Supply Point Connection Information

Our Grid Supply Point Connection Information dataset contains information on each GSP in our region, including proposed new sites, on various connection information. This includes connected capacity to date, transmission reinforcement dates, and technical limit information If you are unsure of any of the column meanings, please hover over the column heading for a description. Related Feature Pages [Major Projects Pipeline] - Our Major Projects Pipeline page provides a view of GSP status and connection queues. Glossary of Terms Our [Glossary] dataset provides definitions for various terms and acronyms found throughout our data. If the term you are searching for isn't in our list, please let us know via our [Open Data team] and we will get it added! Data Governance If you wish to view the data triage document for any dataset, they can be found in our [Data Triage Assessment] dataset. This dataset does NOT require a login to view Any data caveats for the dataset are listed below - None
Grevenbroich: Bevölkerungsdaten 31.12.2025

Die Bevölkerung in den statistischen Bezirken der Stadt Grevenbroich (nach Geschlecht) Stichtag: 31.12.2025 Quelle: Stadt Grevenbroich, FB 61 - Statistik, Melderegisterauswertung, Bevölkerung am Ort der Hauptwohnung
Historic Substation Utilisation (SPEN_030) Data Quality Checks

This data table provides the detailed data quality assessment scores for the Historic Substation Utilisation dataset. The quality assessment was carried out on the 31st of January. 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 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.