cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10581023
title: Global HydroClimatic Data

description: This database was developed in a research study of  “Zarei, M., Destouni, G. A global multi catchment and multi dataset synthesis for water fluxes and storage changes on land. Sci Data 11, Nature, 1333 (2024). https://doi.org/10.1038/s41597-024-04203-1”. The data from all comparative datasets are synthesized into a complete new open access database, named the Global HydroClimatic Database (GHCD), and presenting data and information in five separate folders.

             The zipped file named ‘GHCD Non-Overlapping Catchment Shapefiles.zip’ in Folder 1 contains the study catchment polygon shapefiles, used to extract the associated data from the global datasets and further aggregate them over each catchment to produce the catchment-average data time series. The catchment polygons were obtained from the GSIM database and are renamed according to the catchment names used in the GHCD database. A csv file named ‘Catchment_Info.csv’ in Folder 1 lists the GHCD catchment names, their corresponding name in the GSIM database, the country in which the catchment outlet (hydrometric station) is located, and the catchment area in square kilometers according as reported in the GSIM database.

           Folders 2-5 provide catchment-aggregated monthly and annual time series for the studied variables (P, ET, R, DS, SM, and T) for the 1561 non-overlapping study catchments and the four comparative “Obs”, “Mixed”, “GLDAS”, and “ERA5” datasets included in GHCD. The catchment-wise data time series are exported as “.csv” files, separately for each variable and catchment. Each Dataset folder contains an (i) Annual folder, (ii) Monthly folder, (iii) “DatasetX_AnnualDataSummary.csv” file, and (iv) “Readme_Data Columns and Variable Units.txt” file. Before using the variable time series in the Annual or Monthly folders, GHCD database users are recommended to read the “Readme_Data Columns and Variable Units.txt” file. This file provides complete information that clarifies the variables included in the Annual and Monthly folders, and the associated data source and origin, variable units, and column names of the time series in the CSV files. For the SM variable, the rootzone depth for the soil moisture profile considered in the associated reanalysis product of the “Mixed” (GLEAM), “ERA5”, and “GLDAS” datasets is also reported for possible further applications.  The “DatasetX_AnnualDataSummary.csv” file included in Folders 2-5 also provides brief summary information for all data considered for the 1561 non-overlapping catchments in all comparative datasets included in GHCD. This file also provides catchment-wise long-term average annual values of P, R, ET, DS, DSM, and T for all GHCD catchments. Further this file provides explicit calculated data for the implied CWLC, and also for PETLang, PET/P, ET/P, and R/P as “Quality check data”. The catchment names, the country where the catchment outlet is located, and the catchment area in square kilometers are also provided in this data summary.
DOI: 10.5281/zenodo.10581024
title: Global HydroClimatic Database

description: This database was developed using the data from all comparative datasets which are synthesized into a complete new open access database, named the Global HydroClimatic Database (GHCD), and presenting data and information in five separate folders.
DOI: 10.5281/zenodo.10790401
title: Global HydroClimatic Database

description: This database was developed in a research study of  “A global multi-dataset and multi-catchment database for water fluxes and storage changes on land”. The data from all comparative datasets are synthesized into a complete new open access database, named the Global HydroClimatic Database (GHCD), and presenting data and information in five separate folders.

             The zipped file named ‘GHCD Non-Overlapping Catchment Shapefiles.zip’ in Folder 1 contains the study catchment polygon shapefiles, used to extract the associated data from the global datasets and further aggregate them over each catchment to produce the catchment-average data time series. The catchment polygons were obtained from the GSIM database and are renamed according to the catchment names used in the GHCD database. A csv file named ‘Catchment_Info.csv’ in Folder 1 lists the GHCD catchment names, their corresponding name in the GSIM database, the country in which the catchment outlet (hydrometric station) is located, and the catchment area in square kilometers according as reported in the GSIM database.

           Folders 2-5 provide catchment-aggregated monthly and annual time series for the studied variables (P, ET, R, DS, SM, and T) for the 1561 non-overlapping study catchments and the four comparative “Obs”, “Mixed”, “GLDAS”, and “ERA5” datasets included in GHCD. The catchment-wise data time series are exported as “.csv” files, separately for each variable and catchment. Each Dataset folder contains an (i) Annual folder, (ii) Monthly folder, (iii) “DatasetX_AnnualDataSummary.csv” file, and (iv) “Readme_Data Columns and Variable Units.txt” file. Before using the variable time series in the Annual or Monthly folders, GHCD database users are recommended to read the “Readme_Data Columns and Variable Units.txt” file. This file provides complete information that clarifies the variables included in the Annual and Monthly folders, and the associated data source and origin, variable units, and column names of the time series in the CSV files. For the SM variable, the rootzone depth for the soil moisture profile considered in the associated reanalysis product of the “Mixed” (GLEAM), “ERA5”, and “GLDAS” datasets is also reported for possible further applications.  The “DatasetX_AnnualDataSummary.csv” file included in Folders 2-5 also provides brief summary information for all data considered for the 1561 non-overlapping catchments in all comparative datasets included in GHCD. This file also provides catchment-wise long-term average annual values of P, R, ET, DS, DSM, and T for all GHCD catchments. Further this file provides explicit calculated data for the implied CWLC, and also for PETLang, PET/P, ET/P, and R/P as “Quality check data”. The catchment names, the country where the catchment outlet is located, and the catchment area in square kilometers are also provided in this data summary.
DOI: 10.5281/zenodo.10932898
title: Global HydroClimatic Data

description: This database was developed in a research study of  “Zarei, M., Destouni, G. A global multi catchment and multi dataset synthesis for water fluxes and storage changes on land. Sci Data 11, Nature, 1333 (2024). https://doi.org/10.1038/s41597-024-04203-1”. The data from all comparative datasets are synthesized into a complete new open access database, named the Global HydroClimatic Database (GHCD), and presenting data and information in five separate folders.

             The zipped file named ‘GHCD Non-Overlapping Catchment Shapefiles.zip’ in Folder 1 contains the study catchment polygon shapefiles, used to extract the associated data from the global datasets and further aggregate them over each catchment to produce the catchment-average data time series. The catchment polygons were obtained from the GSIM database and are renamed according to the catchment names used in the GHCD database. A csv file named ‘Catchment_Info.csv’ in Folder 1 lists the GHCD catchment names, their corresponding name in the GSIM database, the country in which the catchment outlet (hydrometric station) is located, and the catchment area in square kilometers according as reported in the GSIM database.

           Folders 2-5 provide catchment-aggregated monthly and annual time series for the studied variables (P, ET, R, DS, SM, and T) for the 1561 non-overlapping study catchments and the four comparative “Obs”, “Mixed”, “GLDAS”, and “ERA5” datasets included in GHCD. The catchment-wise data time series are exported as “.csv” files, separately for each variable and catchment. Each Dataset folder contains an (i) Annual folder, (ii) Monthly folder, (iii) “DatasetX_AnnualDataSummary.csv” file, and (iv) “Readme_Data Columns and Variable Units.txt” file. Before using the variable time series in the Annual or Monthly folders, GHCD database users are recommended to read the “Readme_Data Columns and Variable Units.txt” file. This file provides complete information that clarifies the variables included in the Annual and Monthly folders, and the associated data source and origin, variable units, and column names of the time series in the CSV files. For the SM variable, the rootzone depth for the soil moisture profile considered in the associated reanalysis product of the “Mixed” (GLEAM), “ERA5”, and “GLDAS” datasets is also reported for possible further applications.  The “DatasetX_AnnualDataSummary.csv” file included in Folders 2-5 also provides brief summary information for all data considered for the 1561 non-overlapping catchments in all comparative datasets included in GHCD. This file also provides catchment-wise long-term average annual values of P, R, ET, DS, DSM, and T for all GHCD catchments. Further this file provides explicit calculated data for the implied CWLC, and also for PETLang, PET/P, ET/P, and R/P as “Quality check data”. The catchment names, the country where the catchment outlet is located, and the catchment area in square kilometers are also provided in this data summary.
DOI: 10.15468/dl.s3neen
title: Occurrence Download

description: A dataset containing 8491 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Populus tremuloides Michx.",
 "Geometry POLYGON((-105 38, -80 38, -80 58, -105 58, -105 38))"
 ]
}

 The dataset includes 8491 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020608-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14283984
title: Dataset related to article: FM19G11-LOADED NANOPARTICLES MODULATE ENERGETIC STATUS AND PRODUCTION OF REACTIVE OXYGEN SPECIES IN MYOBLASTS FROM ALS MICE

description: The database inlcudes the CT values obtained from the mrna analysis by realt time pcr. 

in addition the database includes the data obtaiend by mina analysis. specifically, 

MiNA plugin classifies each pixel of a skeleton image and, according to how the pixels are spatially related one to each other, mitochondria are classified as 1) individuals, characterized by rod, punctate or large/round morphology; 2) networks, which are a large continuous reticulum of multiple mitochondria. Each network contains at least one junction and more than one branch. 

MiNA specifically computes the number of individuals, which is the number of objects that does not contain a junction pixel, and corresponds to the number of mitochondria that are not part of a network. Regarding the network analysis, MiNA accurately provides the: 1) number of networks, corresponding to the number of objects that contains at least one junction pixel; the number of networks is indicative of the balance between the fission and fusion processes, where the mitochondria divides into one or more independent structure (individuals), or are fused resulting in thin and elongated highly interconnected mitochondrial network; 2) mean length of network branches; 3) median length of network branches; 4) standard deviation of network branch lengths; 5) mean number of branches per network; 6) median number of branches per network; and 7) standard deviation of the number of branches per network. 

These parameters quantify the extension of the mitochondrial networks and how statistically disperse they are. Finally, MiNA enables the mitochondrial footprint analysis, which calculates the total area or volume of the image consumed by the lengths of mitochondrial structure using a topological skeleton.
DOI: 10.5281/zenodo.14283985
title: Dataset related to article: FM19G11-LOADED NANOPARTICLES MODULATE ENERGETIC STATUS AND PRODUCTION OF REACTIVE OXYGEN SPECIES IN MYOBLASTS FROM ALS MICE

description: The database inlcudes the CT values obtained from the mrna analysis by realt time pcr. 

in addition the database includes the data obtaiend by mina analysis. specifically, 

MiNA plugin classifies each pixel of a skeleton image and, according to how the pixels are spatially related one to each other, mitochondria are classified as 1) individuals, characterized by rod, punctate or large/round morphology; 2) networks, which are a large continuous reticulum of multiple mitochondria. Each network contains at least one junction and more than one branch. 

MiNA specifically computes the number of individuals, which is the number of objects that does not contain a junction pixel, and corresponds to the number of mitochondria that are not part of a network. Regarding the network analysis, MiNA accurately provides the: 1) number of networks, corresponding to the number of objects that contains at least one junction pixel; the number of networks is indicative of the balance between the fission and fusion processes, where the mitochondria divides into one or more independent structure (individuals), or are fused resulting in thin and elongated highly interconnected mitochondrial network; 2) mean length of network branches; 3) median length of network branches; 4) standard deviation of network branch lengths; 5) mean number of branches per network; 6) median number of branches per network; and 7) standard deviation of the number of branches per network. 

These parameters quantify the extension of the mitochondrial networks and how statistically disperse they are. Finally, MiNA enables the mitochondrial footprint analysis, which calculates the total area or volume of the image consumed by the lengths of mitochondrial structure using a topological skeleton.
DOI: 10.5281/zenodo.14284105
title: METAPHORS AND IMAGERY IN THE CONCEPT OF BEAUTY
DOI: 10.5281/zenodo.14284106
title: METAPHORS AND IMAGERY IN THE CONCEPT OF BEAUTY
DOI: 10.15468/dl.cfwfrc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Quercus montana Willd.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Living Specimen"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020609-241126133413365/datasets/export for details.
DOI: 10.25504/fairsharing.1414v8
title: FAIRsharing record for: BRENDA tissue / enzyme source
title: BTO

description: This FAIRsharing record describes:  A structured controlled vocabulary for the source of an enzyme. It comprises terms for tissues, cell lines, cell types and cell cultures from uni- and multicellular organisms.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.2mk2zb
title: FAIRsharing record for: Logical Observation Identifier Names and Codes
title: LOINC

description: This FAIRsharing record describes:  LOINC is a common language (set of identifiers, names, and codes) for clinical and laboratory observations. LOINC is a catalog of measurements, including laboratory tests, clinical measures like vital signs and anthropomorphic measures, standardized survey instruments, and more. LOINC enables the exchange and aggregation of clinical results for care delivery, outcomes management, and research by providing a set of universal codes and structured names to unambiguously identify things you can measure or observe.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.dg76vs
title: FAIRsharing record for: Synthetic Biology Open Language Visual
title: SBOL Visual

description: This FAIRsharing record describes:  Synthetic Biology Open Language Visual (SBOL Visual) is an open-source graphical notation that uses schematic “glyphs” to specify genetic parts, devices, modules, and systems.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.ezznsh
title: FAIRsharing record for: Newick tree Format
title: NWK

description: This FAIRsharing record describes:  The Newick Standard for representing trees in computer-readable form makes use of the correspondence between trees and nested parentheses, noticed in 1857 by the famous English mathematician Arthur Cayley.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.1sgm8q
title: FAIRsharing record for: BioModels Ontology
title: null

description: This FAIRsharing record describes:  The BioModels Ontology is an OWL Representation of the models in the BioModels repository. This resource has not been updated recently within BioPortal, and no official homepage can be found, therefore we have marked its status as Uncertain. Please get in touch with us if you have any information on this project.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.5pp7gn
title: FAIRsharing record for: Minimum Information about a Neuroscience Investigation
title: MINI

description: This FAIRsharing record describes:  This module represents the formalised opinion of the authors and the CARMEN consortium, which identifies the minimum information required to report the use of electrophysiology in a neuroscience study. A MINI module represents the minimum information that should be reported about a dataset to facilitate computational access and analysis to allow a reader to interpret and critically evaluate the processes performed and the conclusions reached, and to support their experimental corroboration. In practice a MINI module comprises a checklist of information that should be provided (for example about the protocols employed) when a data set is submitted to the CARMEN system. Please note that, while these guidelines remain available, the CARMEN project can no longer be accessed. Please let us know if you have any information regarding this resource.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.qtwya6
title: FAIRsharing record for: Material Element component of the SWEET ontology
title: null

description: This FAIRsharing record describes:  Material Element component of SWEET ontology. SWEET is a highly modular ontology suite with many separate ontologies covering Earth system science. SWEET is a mid-level ontology and consists of nine top-level concepts that can be used as a foundation for domain-specific ontologies that extend these top-level SWEET components. 
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.8jns8
title: FAIRsharing record for: e-Mouse Atlas Project Anatomy Ontology
title: EMAP

description: This FAIRsharing record describes:  A structured controlled vocabulary of stage-specific anatomical structures of the mouse used within the e-Mouse Atlas Project.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.qtb9yb
title: FAIRsharing record for: Minimal Anatomical Terminology
title: MAT

description: This FAIRsharing record describes:  Minimal set of terms for anatomy.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.vhgehd
title: FAIRsharing record for: Subcellular Anatomy Ontology
title: SAO

description: This FAIRsharing record describes:  SAO describes structures from the dimensional range encompassing cellular and subcellular structure, supracellular domains, and macromolecules.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.yecp83
title: FAIRsharing record for: Spider Anatomy Ontology
title: SPD

description: This FAIRsharing record describes:  An ontology for spider comparative biology including anatomical parts (e.g. leg, claw), behavior (e.g. courtship, combing) and products (i.g. silk, web, borrow).
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.24yjfc
title: FAIRsharing record for: Habronattus Courtship Ontology
title: HC

description: This FAIRsharing record describes:  A demonstration of ontology construction as a general technique for coding ethograms and other descriptions of behavior into machine understandable forms. An ontology for courtship behavior of the spider Habronattus californicus.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.