cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57745/6oiirs
title: Evolution des niveaux piézométriques en France par niveaux de réchauffement

description: Ce rapport fait suite aux rapports concernant les impacts climatiques analysés selon les différents niveaux de réchauffement fixés par la Trajectoire de Réchauffement de référence pour l’Adaptation au Changement Climatique (TRACC) (Soubeyroux et al. 2024, 2025). Il présente une synthèse des résultats obtenus pour les niveaux piézométriques, issus des projections hydrologiques obtenues à partir de la plate-forme de modélisation hydrogéologique AquiFR et du modèle hydrologique EROS-Bretagne au sein du projet Explore2. Les analyses réalisées portent sur l’évolution des niveaux de nappe en s’appuyant sur plusieurs indicateurs : le calcul des niveaux piézométriques moyens à l’échelle annuelle et saisonnière ainsi que l’identification et la fréquence d’occurrence d’événements extrêmes. Les impacts sont déterminés en agrégeant ces indicateurs sur des fenêtres d’extraction de 20 ans propres à chaque projection mobilisée pour la TRACC et en comparant trois niveaux de réchauffement futurs (+2 °C, +2.7 °C et +4 °C) à une période de référence historique (1976-2005). Les réponses à trois grands types d’évolution climatique (limitée, contrastée ou sèche) possibles pour une France à +4 °C illustrent les incertitudes. Ce document complète les analyses portant sur la recharge potentielle et les débits, établies dans le rapport de Sauquet et al. (2025). La synthèse de ces résultats montre une forte dispersion entre projections sur la partie nord du domaine AquiFR (désaccord sur le signe du changement entre modèles) avec toutefois une augmentation globale des niveaux de nappe suggérée par la médiane des modèles, et un accord des modèles pour une baisse des niveaux de nappe sur la partie sud du domaine AquiFR (Tarn-et-Garonne) et sur la Bretagne. Ces tendances s’accentuent avec des niveaux de réchauffement. Les résultats relatifs aux extrêmes hydrologiques confortent et complètent ces conclusions. On retrouve pour le niveau de réchauffement à +4 °C : (i) un asséchement des nappes en Bretagne et dans le sud de la France (Tarn-et-Garonne), illustré par une hausse du nombre d’occurrences d’événements secs dans ces régions et (ii) une amplification du nombre d’occurrences d’événements humides dans le nord de la France, qui reste cependant marquée par une forte dispersion entre les modèles. Les réponses observées aux trois grands types d’évolution climatique (limitée, contrastée ou sèche) pour une France à +4 °C confortent ces conclusions et sont en accord avec les hypothèses propres à chacun de ces scénarios. Elles mettent en avant l’assèchement futur des nappes sur la Bretagne et sur le territoire Tarn-et-Garonne. Ces résultats semblent cohérents avec les tendances d’évolution de recharge potentielle fournies par Lanini et al. (2024).
DOI: 10.5281/zenodo.18479408
title: Counterion-Induced Conformational Effects in Catalysts

description: Please find the supporting information for the "Counterion-Induced Conformational Effects in Catalysts" study here.
DOI: 10.15468/dl.28phz3
title: Occurrence Download

description: A dataset containing 2687 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phyllotreta vittula",
 "BasisOfRecord is Human Observation",
 "Year is greater than or equal to 1990",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 2687 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011247-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18479407
title: Counterion-Induced Conformational Effects in Catalysts

description: Please find the supporting information for the "Counterion-Induced Conformational Effects in Catalysts" study here.
DOI: 10.15468/dl.bv7pq5
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Prieskum obojživelníkov a plazov, Chopok juh, lyžiarske stredisko"
 ]
}

 The dataset includes 13 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011249-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4nukpe
title: Occurrence Download

description: A dataset containing 153 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tripterocalyx carneus",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 153 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011250-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31082683
title: Raw datasets on soil salinity, fatty acid composition, and antioxidant properties of rice bran oil from northeastern Thailand

description: <b>File 1 – Soil data</b>Raw soil chemical properties and site information for rice cultivation sites along the Siao Yai River basin, northeastern Thailand.<b>File 2 – RBO yield & bioactive compounds</b>Raw data for rice bran oil yield, bioactive compounds, and antioxidant activity from RD6 and KDML105 grown under low- and high-salinity conditions at rice cultivation sites.<b>File 3 – Fatty acid composition (GC–MS)</b>Raw GC–MS–derived individual fatty acid methyl ester composition data of rice bran oil from RD6 and KDML105 cultivated under contrasting soil salinity conditions.<b>File 4 – RBO elemental composition</b>Raw elemental concentration data of rice bran oil measured by atomic absorption spectroscopy from rice cultivated under low- and high-salinity soil conditions.<b>File 5 – Correlation & PCA dataset</b>Raw and processed datasets used for Pearson correlation and principal component analyses linking soil properties with rice bran oil quality traits.
DOI: 10.6084/m9.figshare.31082683.v1
title: Raw datasets on soil salinity, fatty acid composition, and antioxidant properties of rice bran oil from northeastern Thailand

description: <b>File 1 – Soil data</b>Raw soil chemical data and site information for rice fields along the Siao Yai River basin, northeastern Thailand. Variables were used to classify soil salinity and support soil–oil relationship analyses.<b>File 2 – RBO yield & bioactive compounds</b>Raw data for rice bran oil yield, bioactive compounds, and antioxidant activity from RD6 and KDML105 grown under low- and high-salinity conditions.<b>File 3 – Fatty acid composition (GC–MS)</b>Raw GC–MS–derived fatty acid methyl ester composition data of rice bran oil from RD6 and KDML105 cultivated under contrasting soil salinity conditions.<b>File 4 – RBO mineral elements</b>Raw mineral element concentration data of rice bran oil measured by atomic absorption spectroscopy from rice grown under low- and high-salinity soils.<b>File 5 – Correlation & PCA dataset</b>Integrated dataset used for Pearson correlation and principal component analyses linking soil properties with rice bran oil quality traits.
DOI: 10.6084/m9.figshare.31082683.v2
title: Raw datasets on soil salinity, fatty acid composition, and antioxidant properties of rice bran oil from northeastern Thailand

description: <b>File 1 – Soil data</b>Raw soil chemical properties and site information for rice cultivation sites along the Siao Yai River basin, northeastern Thailand.<b>File 2 – RBO yield & bioactive compounds</b>Raw data for rice bran oil yield, bioactive compounds, and antioxidant activity from RD6 and KDML105 grown under low- and high-salinity conditions at rice cultivation sites.<b>File 3 – Fatty acid composition (GC–MS)</b>Raw GC–MS–derived individual fatty acid methyl ester composition data of rice bran oil from RD6 and KDML105 cultivated under contrasting soil salinity conditions.<b>File 4 – RBO elemental composition</b>Raw elemental concentration data of rice bran oil measured by atomic absorption spectroscopy from rice cultivated under low- and high-salinity soil conditions.<b>File 5 – Correlation & PCA dataset</b>Raw and processed datasets used for Pearson correlation and principal component analyses linking soil properties with rice bran oil quality traits.
DOI: 10.15468/dl.crynm5
title: Occurrence Download

description: A dataset containing 3774 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ajuga pyramidalis, Ajuga pyramidalis, Ajuga pyramidalis)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 3774 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011251-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15301819
title: Centrifugal Pump Dataset

description: Description

This dataset contains operational data recorded from centrifugal pumps that supply demineralized water to the boilers of a heating plant. The plant provides the steam required by the research test facilities at CIRA (Italian Aerospace Research Centre).

The dataset includes eigth CSV files, each representing data collected from a specific centrifugal pump during a single operational day. Filenames uniquely identify both the pump unit (A, B, or C) and the corresponding day of operation. For example, the file A_2024-04-10.csv contains the recorded data for centrifugal pump A on April 10, 2024. At the time of writing, the dataset includes records from three distinct operational days, each covering a different time span.

Note: Data for pump C is not available for October 30, 2024, as the pump was turned off on that day.

Each CSV file contains 11 columns: one for the timestamp and ten for measured values. The column headers include the following names, as listed in the following Table, where the prefix X represents the centrifugal pump unit label (e.g., A, B, or C):




Column Name
Description
Unit of Measure


Timestamp
temporal timestamp indicating when the measurement was taken, formatted as YYYY-MM-DD hh:mm:ss
-


X_ACR_Mot.PV
vibrational velocity measured by the motor accelerometer
m/s


X_ACR_Mot.SV
peak value measured by the motor accelerometer
m/s2


X_ACR_Mot.TV
contact temperature of the motor accelerometer
°C


X_ACR_Pmp.PV
vibrational velocity measured by the pump accelerometer
m/s


X_ACR_Pmp.SV
peak value measured by the pump accelerometer
m/s2


X_ACR_Pmp.TV
contact temperature of the pump accelerometer
°C


X_Temp.SV
motor casing temperature
°C


X_Pres.SV
outlet fluid pressure from the pump
bar


Barometer
atmospheric pressure
mbar


Temperature
ambient temperature
°C




 

The nameplate data of the motor and pump are reported in the following table:




 
 
Electric Motor
 
 


Power Shaft
Speed
Voltage
Poles
Frame Size (H)


110 kW
2980 rpm
400 V
 2
315 mm


 
 
Mechanical Multistage Pump
 
 


Power
Flow Rate
Pump Head
Max Pressure
N° of Impellers


10 kW
45 m3/h
450 m
40 bar
7




 

For any inquiries or issues regarding the dataset, please contact a.martone@cira.it and/or g.zazzaro@cira.it

Data were collected as part of the SACIP (SAlus CIra Plant) project, funded by the Italian PRORA.
DOI: 10.5281/zenodo.18479728
title: Centrifugal Pump Dataset

description: Description

This dataset contains operational data recorded from centrifugal pumps that supply demineralized water to the boilers of a heating plant. The plant provides the steam required by the research test facilities at CIRA (Italian Aerospace Research Centre).

The dataset includes eigth CSV files, each representing data collected from a specific centrifugal pump during a single operational day. Filenames uniquely identify both the pump unit (A, B, or C) and the corresponding day of operation. For example, the file A_2024-04-10.csv contains the recorded data for centrifugal pump A on April 10, 2024. At the time of writing, the dataset includes records from three distinct operational days, each covering a different time span.

Note: Data for pump C is not available for October 30, 2024, as the pump was turned off on that day.

Each CSV file contains 11 columns: one for the timestamp and ten for measured values. The column headers include the following names, as listed in the following Table, where the prefix X represents the centrifugal pump unit label (e.g., A, B, or C):




Column Name
Description
Unit of Measure


Timestamp
temporal timestamp indicating when the measurement was taken, formatted as YYYY-MM-DD hh:mm:ss
-


X_ACR_Mot.PV
vibrational velocity measured by the motor accelerometer
m/s


X_ACR_Mot.SV
peak value measured by the motor accelerometer
m/s2


X_ACR_Mot.TV
contact temperature of the motor accelerometer
°C


X_ACR_Pmp.PV
vibrational velocity measured by the pump accelerometer
m/s


X_ACR_Pmp.SV
peak value measured by the pump accelerometer
m/s2


X_ACR_Pmp.TV
contact temperature of the pump accelerometer
°C


X_Temp.SV
motor casing temperature
°C


X_Pres.SV
outlet fluid pressure from the pump
bar


Barometer
atmospheric pressure
mbar


Temperature
ambient temperature
°C




 

The nameplate data of the motor and pump are reported in the following table:




 
 
Electric Motor
 
 


Power Shaft
Speed
Voltage
Poles
Frame Size (H)


110 kW
2980 rpm
400 V
 2
315 mm


 
 
Mechanical Multistage Pump
 
 


Power
Flow Rate
Pump Head
Max Pressure
N° of Impellers


10 kW
45 m3/h
450 m
40 bar
7




 

For any inquiries or issues regarding the dataset, please contact a.martone@cira.it and/or g.zazzaro@cira.it

Data were collected as part of the SACIP (SAlus CIra Plant) project, funded by the Italian PRORA.
DOI: 10.15468/dl.gcebz4
title: Occurrence Download

description: A dataset containing 187 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Callosobruchus chinensis",
 "BasisOfRecord is Human Observation",
 "Year is greater than or equal to 1990",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 187 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011253-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18479711
title: Gloria Taitano (LiDAR) May 27 2025

description: This orthomosaic of Talo'fo'fo', Guam was created from 20 images taken on May 27 2025, at 200ft AGL, with a DJI Matrice 350 . The mission was planned using the DJI Pilot application and post-processed using DJI Terra.

This project was made possible through funding by the following grant(s): NACD (Award No. HQ00342020012).
description: Disclaimer: The following aerial imagery is intended solely for research purposes related to the assessment of the captured area. It is strictly prohibited to distribute this imagery to any unauthorized individuals or third-party entities without prior authorization. All drone imagery was obtained in accordance with FAA guidelines and applicable local laws, with all necessary authorizations secured to ensure safe and legal operation.

The University of Guam Drone Corps funded by NASA Guam Space Grant and NASA Guam EPSCoR retain all rights to the aerial imagery, including but not limited to copyrights and intellectual property rights. Any unauthorized modification, reproduction, or distribution of the imagery is strictly prohibited.

By using this data, you acknowledge and agree to abide by the terms and conditions set forth in this disclaimer.

 

 

Privacy Disclaimer: The aerial imagery captured for assessment may inadvertently include images of private property and individuals. While every effort has been made to respect privacy, it is possible that identifiable information or sensitive locations may be visible in the imagery. University of Guam Drone Corps and related parties disclaim any responsibility for the unintentional collection or dissemination of such information. The recipient(s) of this imagery are urged to handle it with due care and take necessary precautions to protect the privacy rights of individuals and comply with applicable privacy laws and regulations.
DOI: 10.15468/dl.q759dc
title: Occurrence Download

description: A dataset containing 20156 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Geometry POLYGON((-177.77995 13.49939,-34.36764 13.49939,-34.36764 75.63707,-177.77995 75.63707,-177.77995 13.49939))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Larix laricina"
 ]
}

 The dataset includes 20156 records from 140 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005513-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18457887
title: High-Resolution Seawater Greenhouse Gas Observations in Mangrove creeks and Seagrass meadows in Zanzibar (Tanzania)

description: This dataset presents field observations of seawater from a tidal seagrass meadow (Enhalus acoroides Linnaeus f.) and a tidal mangrove (dominated by Avicennia marina, (Shunula, 1996)) creek in Chwaka Bay, Tanzania. Measurements were collected during the wet season (November–December 2022) in a high temporal resolution. The dataset includes time series measurements of dissolved carbon dioxide (CO2) and methane (CH4), along with water depth, temperature, salinity, dissolved oxygen, pH, and radon concentration. All timestamps are reported in East Africa Time (EAT; UTC+03:00).

Time series observations of CO2 and CH4 were measured using automated greenhouse gas analyzers (LI-COR LI-7810; 1 second intervals). The groundwater tracer radon measurements were performed with a radon-in-air analyzer (RAD7 Durridge Company; 30 minutes interval). Both instruments operated in a closed air loop equilibrated with a continuous stream of seawater (~3 L per minute) pumped through a showerhead gas exchanger (Santos et al., 2012). Water depth, water temperature and salinity (Solinst 3001 Levelogger 5), dissolved oxygen (MiniDOT oxygen logger, PME), and pH (HOBO MX2501 pH and Temperature Data Logger, ONSET) loggers were all calibrated before use.

For consistency, all measurements were subsequently averaged to 15-minute intervals. The reported data were corrected for analytical time lags of 10 min for CO2, 30 min for CH4 and 30 min for radon concentrations.

 

References

Santos, I. R., Maher, D. T., & Eyre, B. D. (2012). Coupling Automated Radon and Carbon Dioxide Measurements in Coastal Waters. Environmental Science & Technology, 46(14), 7685-7691. https://doi.org/10.1021/es301961b

Shunula, J. P. T. (1996). Ecological studies on selected mangrove swamps in Zanzibar. Master dissertation, University of Dar es Salaam. Available at (http://41.86.178.3/internetserver3.1.2/search.aspx?formtype=advanced)

Funding

The production of this data-set was funded by a grant from VR-Sida 2019-04038 and partially funded by Swedish Research Council Vetenskapsrådet (2019‐03930, 2020‐00457).

Acknowledgement.

Thanks to fishermen Abdallah Hamisi Juma and Abeid Hamis Juma and hostest Mariam Msami for helping us in field and hosting us as well as Chwaka village, Zanzibar Tanzania.
DOI: 10.5281/zenodo.18457886
title: High-Resolution Seawater Greenhouse Gas Observations in Mangrove creeks and Seagrass meadows in Zanzibar (Tanzania)

description: This dataset presents field observations of seawater from a tidal seagrass meadow (Enhalus acoroides Linnaeus f.) and a tidal mangrove (dominated by Avicennia marina, (Shunula, 1996)) creek in Chwaka Bay, Tanzania. Measurements were collected during the wet season (November–December 2022) in a high temporal resolution. The dataset includes time series measurements of dissolved carbon dioxide (CO2) and methane (CH4), along with water depth, temperature, salinity, dissolved oxygen, pH, and radon concentration. All timestamps are reported in East Africa Time (EAT; UTC+03:00).

Time series observations of CO2 and CH4 were measured using automated greenhouse gas analyzers (LI-COR LI-7810; 1 second intervals). The groundwater tracer radon measurements were performed with a radon-in-air analyzer (RAD7 Durridge Company; 30 minutes interval). Both instruments operated in a closed air loop equilibrated with a continuous stream of seawater (~3 L per minute) pumped through a showerhead gas exchanger (Santos et al., 2012). Water depth, water temperature and salinity (Solinst 3001 Levelogger 5), dissolved oxygen (MiniDOT oxygen logger, PME), and pH (HOBO MX2501 pH and Temperature Data Logger, ONSET) loggers were all calibrated before use.

For consistency, all measurements were subsequently averaged to 15-minute intervals. The reported data were corrected for analytical time lags of 10 min for CO2, 30 min for CH4 and 30 min for radon concentrations.

 

References

Santos, I. R., Maher, D. T., & Eyre, B. D. (2012). Coupling Automated Radon and Carbon Dioxide Measurements in Coastal Waters. Environmental Science & Technology, 46(14), 7685-7691. https://doi.org/10.1021/es301961b

Shunula, J. P. T. (1996). Ecological studies on selected mangrove swamps in Zanzibar. Master dissertation, University of Dar es Salaam. Available at (http://41.86.178.3/internetserver3.1.2/search.aspx?formtype=advanced)

Funding

The production of this data-set was funded by a grant from VR-Sida 2019-04038 and partially funded by Swedish Research Council Vetenskapsrådet (2019‐03930, 2020‐00457).

Acknowledgement.

Thanks to fishermen Abdallah Hamisi Juma and Abeid Hamis Juma and hostest Mariam Msami for helping us in field and hosting us as well as Chwaka village, Zanzibar Tanzania.
DOI: 10.15468/dl.kgesd6
title: Occurrence Download

description: A dataset containing 935 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hilleria latifolia",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 935 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011254-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18479750
title: SModelS analyses json for HEPData

description: Json file specifying the analyses implemented in the SModelS database, adapted for HEPData linking.
description: Version v1 corresponds to the full v3.0.0 database including superseded analyses (official300+superseded300).

Latest version (v3) corresponds to the full v3.1.1 database including superseded analyses (official311+superseded311).
DOI: 10.5281/zenodo.13952091
title: SModelS analyses json for HEPData

description: Json file specifying the analyses implemented in the SModelS database, adapted for HEPData linking.
description: Version v1 corresponds to the full v3.0.0 database including superseded analyses (official300+superseded300).

Latest version (v3) corresponds to the full v3.1.1 database including superseded analyses (official311+superseded311).
DOI: 10.5281/zenodo.18479731
title: London Public Transport

description: By extending the Neo4j Hands On Lab - Creating a Graph of the London Public Transportation Network, we provide CSV files and a Neo4J Cypher script to create a graph that models London's public transport network.
DOI: 10.5281/zenodo.18479732
title: London Public Transport

description: By extending the Neo4j Hands On Lab - Creating a Graph of the London Public Transportation Network, we provide CSV files and a Neo4J Cypher script to create a graph that models London's public transport network.