cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14182902
title: Coordinated Great Lakes lake-wide average monthly mean water levels

description:  

This dataset consists of lake-wide average monthly mean water levels for Lakes Superior, Michigan-Huron, Saint Clair, Erie, and Ontario. The data are presented in meters with reference to the International Great Lakes Datum (IGLD) 1985. The dataset is computed and stewarded by Environment and Climate Change Canada (ECCC) and the United States Army Corps of Engineers (USACE), under the auspices of the Coordinating Committee on Great Lakes Basic Hydraulic and Hydrologic Data (Coordinating Committee)1. Each agency independently computes and manages their own version of the dataset. The data are binationally coordinated annually, where ECCC and USACE compare their versions to verify that they are consistent. 

 




The lake-wide average monthly mean water levels are computed from daily hydrometric observations collected from a network of gauging stations located around each lake and on both sides of the Canada-United States border. The gauges are owned and maintained by the Canadian Hydrographic Service (CHS)2 and the National Oceanic and Atmospheric Administration (NOAA)3.  

 




Detailed metadata and data files for each lake are provided within this dataset. The data files are in comma separated value format (CSV). The CSV data files contain both the lake-wide average monthly mean water level and concise metadata described in accordance with the Climate and Forecasting (CF) conventions. The detailed metadata is in PDF format and provides extended descriptions of data sources, computation methods, dataset history, and related information for each great lake.   

 

This dataset is updated annually with the addition of the most recent complete calendar year of data.  The version number reflects the year of the last available data.  However, note that as well as adding the most recent data, data from previous years may be adjusted based on updated information from those years.




 

1Coordinating Committee on Great Lakes Basic Hydraulic and Hydrologic Data https://www.greatlakescc.org/en/home/ 

 




2DFO 2024. Marine Environmental Data Section Archive, https://meds-sdmm.dfo-mpo.gc.ca, Ecosystem and Oceans Science, Department of Fisheries and Oceans Canada. 

 




3NOAA 2024. Tides and Currents, https://tidesandcurrents.noaa.gov/, Center for Operational Oceanographic Products and Services, National Oceanic and Atmospheric Administration.
DOI: 10.5281/zenodo.17428224
title: Coordinated Great Lakes lake-wide average monthly mean water levels

description:  

This dataset consists of lake-wide average monthly mean water levels for Lakes Superior, Michigan-Huron, Saint Clair, Erie, and Ontario. The data are presented in meters with reference to the International Great Lakes Datum (IGLD) 1985. The dataset is computed and stewarded by Environment and Climate Change Canada (ECCC) and the United States Army Corps of Engineers (USACE), under the auspices of the Coordinating Committee on Great Lakes Basic Hydraulic and Hydrologic Data (Coordinating Committee)1. Each agency independently computes and manages their own version of the dataset. The data are binationally coordinated annually, where ECCC and USACE compare their versions to verify that they are consistent. 

 




The lake-wide average monthly mean water levels are computed from daily hydrometric observations collected from a network of gauging stations located around each lake and on both sides of the Canada-United States border. The gauges are owned and maintained by the Canadian Hydrographic Service (CHS)2 and the National Oceanic and Atmospheric Administration (NOAA)3.  

 




Detailed metadata and data files for each lake are provided within this dataset. The data files are in comma separated value format (CSV). The CSV data files contain both the lake-wide average monthly mean water level and concise metadata described in accordance with the Climate and Forecasting (CF) conventions. The detailed metadata is in PDF format and provides extended descriptions of data sources, computation methods, dataset history, and related information for each great lake.   

 

This dataset is updated annually with the addition of the most recent complete calendar year of data.  The version number reflects the year of the last available data.  However, note that as well as adding the most recent data, data from previous years may be adjusted based on updated information from those years.




 

1Coordinating Committee on Great Lakes Basic Hydraulic and Hydrologic Data https://www.greatlakescc.org/en/home/ 

 




2DFO 2024. Marine Environmental Data Section Archive, https://meds-sdmm.dfo-mpo.gc.ca, Ecosystem and Oceans Science, Department of Fisheries and Oceans Canada. 

 




3NOAA 2024. Tides and Currents, https://tidesandcurrents.noaa.gov/, Center for Operational Oceanographic Products and Services, National Oceanic and Atmospheric Administration.
DOI: 10.5281/zenodo.17106632
title: RE-SAMPLE Synthetic ML Training Dataset

description: Synthetic version of the RE-SAMPLE ML training dataset. Created based on data from Fondazione Policlinico Universitario Agostino Gemelli (Gemelli), Medisch Spectrum Twente (MST) and Tartu University Hospital (TUK). The distributions of the variables in the synthetic dataset closely approximate those observed in the original datasets collected during the project. However, some discrepancies exist. Notably, the dataset provided by the partner Gemelli exhibited a significantly higher proportion of missing physical activity data (~87%), whereas the datasets from MST and TUK contained approximately 39% and 28% missing values for this variable, respectively. As a result, the distribution of physical activity in the synthetic dataset deviates more substantially from the real dataset for Gemelli compared to the other partners.
DOI: 10.5281/zenodo.17106631
title: RE-SAMPLE Synthetic ML Training Dataset

description: Synthetic version of the RE-SAMPLE ML training dataset. Created based on data from Fondazione Policlinico Universitario Agostino Gemelli (Gemelli), Medisch Spectrum Twente (MST) and Tartu University Hospital (TUK). The distributions of the variables in the synthetic dataset closely approximate those observed in the original datasets collected during the project. However, some discrepancies exist. Notably, the dataset provided by the partner Gemelli exhibited a significantly higher proportion of missing physical activity data (~87%), whereas the datasets from MST and TUK contained approximately 39% and 28% missing values for this variable, respectively. As a result, the distribution of physical activity in the synthetic dataset deviates more substantially from the real dataset for Gemelli compared to the other partners.
DOI: 10.15468/dl.x39f6y
title: Occurrence Download

description: A dataset containing 530 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (South America, North America)",
 "TaxonKey is Rhinoclemmys punctularia"
 ]
}

 The dataset includes 530 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053122-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n8s6gp
title: Occurrence Download

description: A dataset containing 261 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Picea smithiana",
 "HasCoordinate is true"
 ]
}

 The dataset includes 261 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053125-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hk998h
title: Occurrence Download

description: A dataset containing 4459 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Denmark",
 "OccurrenceStatus is Present",
 "TaxonKey is Anthocharis cardamines",
 "Year 2023-2025"
 ]
}

 The dataset includes 4459 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053127-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mch92y
title: Occurrence Download

description: A dataset containing 440293 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CAN.2_1",
 "Year 2025-2025"
 ]
}

 The dataset includes 440293 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053113-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c51n7z11j
title: MassIVE MSV000099572 - GNPS - Krameria cistoidea - Chile - 2025
title: Extracto de Acetato de etilo activo de Krameria cistoidea
DOI: 10.5281/zenodo.15583426
title: NHIF Bulgaria. Expenditures and Patient Counts for Home Treatment Medicines and Medical Products 2021-2024 (by Region, NHIF Code, and ICD Code)

description: 📊 Dataset Description

This dataset contains detailed records of pharmaceutical expenditures and patient counts for home treatment in Bulgaria, as reported by the National Health Insurance Fund (NHIF). The data covers all reimbursed medicinal products, medical devices, and dietary foods for special medical purposes.

The data is aggregated at the pharmacy level, nested within Regional Health Insurance Offices (RZOK), and grouped by NHIF reimbursement codes and ICD diagnosis codes.

Temporal Granularity:Each month is represented by three reporting time points:





First 10 days




Middle 10 days




Final days of the month



This allows for intra-month analysis of dispensing and expenditure patterns, which is useful for identifying trends, delays, or spikes in utilization.

Structure:





📦 Rows: 5,252,372




📁 Columns: 17




📆 Time period: Monthly data, e.g. from April 2021 onward




🌍 Geography: All NHIF regional offices (RZOK), Bulgaria



Variables:




Variable
Description




region_num
NHIF regional code (2-digit, e.g. 01)


region_name
Name of the NHIF regional office (in Bulgarian)


atc_code
ATC classification code of the product


atc_name
Generic name of the active substance (in Latin)


nhif_code
NHIF-specific reimbursement product code


market_name
Marketed product name (brand name)


packaging
Dosage form and packaging format (e.g. "capsules")


concentration
Concentration or dosage per unit (e.g. "20 mg")


num_in_pack
Number of units per package (e.g. "x28")


icd_code
ICD-10 code of the diagnosed disease (e.g. "K74.3")


icd_name
Diagnosis name in Bulgarian


patients_num
Number of patients reimbursed for the product during the period


pack_num
Number of reimbursed packages


costs
Total public expenditure in BGN (Bulgarian leva)


period
Internal code used to trace data source batch


date_str
Period in compact format (e.g. "apr2021")


date
Standardized date value (first day of the month)




Usage Notes:





The dataset is aggregated monthly and is suitable for time series analysis, pharmacoepidemiology, regional inequality studies, and health economics research.




Product names and diagnoses are in Bulgarian, while ATC codes follow international classification.




Data cleaning and harmonization (e.g. standardization of packaging terms) may be required for some analyses.



License:Unless otherwise restricted by NHIF, this dataset is shared under CC BY 4.0.
DOI: 10.5281/zenodo.17428116
title: NHIF Bulgaria. Expenditures and Patient Counts for Home Treatment Medicines and Medical Products 2021-2024 (by Region, NHIF Code, and ICD Code)

description: 📊 Dataset Description

This dataset contains detailed records of pharmaceutical expenditures and patient counts for home treatment in Bulgaria, as reported by the National Health Insurance Fund (NHIF). The data covers all reimbursed medicinal products, medical devices, and dietary foods for special medical purposes.

The data is aggregated at the pharmacy level, nested within Regional Health Insurance Offices (RZOK), and grouped by NHIF reimbursement codes and ICD diagnosis codes.

Temporal Granularity:Each month is represented by three reporting time points:





First 10 days




Middle 10 days




Final days of the month



This allows for intra-month analysis of dispensing and expenditure patterns, which is useful for identifying trends, delays, or spikes in utilization.

Structure:





📦 Rows: 5,252,372




📁 Columns: 17




📆 Time period: Monthly data, e.g. from April 2021 onward




🌍 Geography: All NHIF regional offices (RZOK), Bulgaria



Variables:




Variable
Description




region_num
NHIF regional code (2-digit, e.g. 01)


region_name
Name of the NHIF regional office (in Bulgarian)


atc_code
ATC classification code of the product


atc_name
Generic name of the active substance (in Latin)


nhif_code
NHIF-specific reimbursement product code


market_name
Marketed product name (brand name)


packaging
Dosage form and packaging format (e.g. "capsules")


concentration
Concentration or dosage per unit (e.g. "20 mg")


num_in_pack
Number of units per package (e.g. "x28")


icd_code
ICD-10 code of the diagnosed disease (e.g. "K74.3")


icd_name
Diagnosis name in Bulgarian


patients_num
Number of patients reimbursed for the product during the period


pack_num
Number of reimbursed packages


costs
Total public expenditure in BGN (Bulgarian leva)


period
Internal code used to trace data source batch


date_str
Period in compact format (e.g. "apr2021")


date
Standardized date value (first day of the month)




Usage Notes:





The dataset is aggregated monthly and is suitable for time series analysis, pharmacoepidemiology, regional inequality studies, and health economics research.




Product names and diagnoses are in Bulgarian, while ATC codes follow international classification.




Data cleaning and harmonization (e.g. standardization of packaging terms) may be required for some analyses.



License:Unless otherwise restricted by NHIF, this dataset is shared under CC BY 4.0.
DOI: 10.15468/dl.bajtm5
title: Occurrence Download

description: A dataset containing 11880 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Colombia",
 "TaxonKey is Cerdocyon thous"
 ]
}

 The dataset includes 11880 records from 335 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053130-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fwpvcp
title: Occurrence Download

description: A dataset containing 787 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (South America, North America)",
 "TaxonKey is Rhinoclemmys melanosterna"
 ]
}

 The dataset includes 787 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053132-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ruyz2k
title: Occurrence Download

description: A dataset listing the 6 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Thyroptera tricolor"
 ]
}

 The dataset's 6 records were derived from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053123-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3sv3vh
title: Occurrence Download

description: A dataset containing 110502 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hemidactylus agrius, Hemidactylus brasilianus, Lygodactylus klugei, Gymnodactylus amarali, Gymnodactylus geckoides, Phyllopezus pollicaris, Coleodactylus brachystoma, Coleodactylus meridionalis, Gonatodes humeralis, Brasiliscincus caissara, Brasiliscincus heathi, Copeoglossum arajara, Copeoglossum nigropunctatum, Notomabuya frenata, Anolis brasiliensis, Anolis meridionalis, Hoplocercus spinosus, Iguana iguana, Enyalius bibronii, Polychrus acutirostris, Stenocercus squarrosus, Tropidurus helenae, Tropidurus hispidus, Tropidurus jaguaribanus, Tropidurus oreadicus, Tropidurus semitaeniatus, Calyptommatus confusionibus, Micrablepharus maximiliani, Nothobachia ablephara, Procellosaurinus erythrocercus, Vanzosaura multiscutata, Colobosaura modesta, Colobosauroides carvalhoi, Colobosauroides cearensis, Ameiva ameiva, Ameivula confusioniba, Ameivula ocellifera, Ameivula xacriaba, Glaucomastix venetacauda, Kentropyx calcarata, Salvator merianae, Tupinambis quadrilineatus, Tupinambis teguixin)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Human Observation, Specimen, Machine Observation, Material sample, Fossil, Observation, Living Specimen, Material citation)"
 ]
}

 The dataset includes 110502 records from 509 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053121-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc1kphyp
title: CCDC 1450643: Experimental Crystal Structure Determination

description: Related Article: Alejandra Arroyave, Anders Lennartson, Alina Dragulescu-Andrasi, Kasper S. Pedersen, Stergios Piligkos, Sebastian A. Stoian, Samuel M. Greer, Chongin Pak, Oleksandr Hietsoi, Hoa Phan, Stephen Hill, Christine J. McKenzie, and Michael Shatruk|2016|Inorg.Chem.|55|5904|doi:10.1021/acs.inorgchem.6b00246
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1kphzq
title: CCDC 1450644: Experimental Crystal Structure Determination

description: Related Article: Alejandra Arroyave, Anders Lennartson, Alina Dragulescu-Andrasi, Kasper S. Pedersen, Stergios Piligkos, Sebastian A. Stoian, Samuel M. Greer, Chongin Pak, Oleksandr Hietsoi, Hoa Phan, Stephen Hill, Christine J. McKenzie, and Michael Shatruk|2016|Inorg.Chem.|55|5904|doi:10.1021/acs.inorgchem.6b00246
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1kpj1t
title: CCDC 1450646: Experimental Crystal Structure Determination

description: Related Article: Alejandra Arroyave, Anders Lennartson, Alina Dragulescu-Andrasi, Kasper S. Pedersen, Stergios Piligkos, Sebastian A. Stoian, Samuel M. Greer, Chongin Pak, Oleksandr Hietsoi, Hoa Phan, Stephen Hill, Christine J. McKenzie, and Michael Shatruk|2016|Inorg.Chem.|55|5904|doi:10.1021/acs.inorgchem.6b00246
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1kpj81
title: CCDC 1450653: Experimental Crystal Structure Determination

description: Related Article: E.E.Netreba, N.V.Somov|2017|Zh.Strukt.Khim.|58|838|doi:10.1134/S0022476617040321
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc1kpltn
title: CCDC 1450732: Experimental Crystal Structure Determination

description: Related Article: Peter L. Dunn, Rebecca K. Carlson, Laura Gagliardi, Ian A. Tonks|2016|Dalton Trans.|45|9892|doi:10.1039/C6DT00431H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1kpj92
title: CCDC 1450654: Experimental Crystal Structure Determination

description: Related Article: Richard A. O'Brien, Manuel Sanchez Zayas, Stephen T. Nestor, Jamie C. Gaitor, Lauran M. Paul, Forrest A. Edhegard, Samuel Minkowicz, Richard E. Sykora, Yinghong Sheng, Scott F. Michael, Sharon Isern, Arsalan Mirjafari|2016|New J.Chem.|40|7795|doi:10.1039/C6NJ00657D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc1kplvp
title: CCDC 1450733: Experimental Crystal Structure Determination

description: Related Article: Peter L. Dunn, Rebecca K. Carlson, Laura Gagliardi, Ian A. Tonks|2016|Dalton Trans.|45|9892|doi:10.1039/C6DT00431H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc1kplwq
title: CCDC 1450734: Experimental Crystal Structure Determination

description: Related Article: Peter L. Dunn, Rebecca K. Carlson, Laura Gagliardi, Ian A. Tonks|2016|Dalton Trans.|45|9892|doi:10.1039/C6DT00431H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc1kplxr
title: CCDC 1450735: Experimental Crystal Structure Determination

description: Related Article: Peter L. Dunn, Rebecca K. Carlson, Laura Gagliardi, Ian A. Tonks|2016|Dalton Trans.|45|9892|doi:10.1039/C6DT00431H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.