cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18150/skxdxn
title: Agomelatine release from ethanol gel-coated arrow microneedle systems

description: Raw data from release studies of agomelatine (AGM) from microneedle systems.Microneedle system specifications:3D printing method: Digital Light Processing (DLP)microneedle shape: Arrowcoating-gel type: ethanol gelDrug release studies:The permeation of agomelatine (AGM) was evaluated using Franz Diffusion Cells (Teledyne Hanson 376 Research, USA) with full-thickness human skin as the diffusion membrane.Quantification of AGM:The amount of AGM permeated was analyzed using High-Performance Liquid Chromatography (HPLC) (Shimadzu Nexera-I LC-2040C, Japan) with LabSolution Lite software.Chromatographic Conditions:Column: Reversed-phase C18 (HyperClone BDS C18, 5 µm, 4.6 × 250 mm, Phenomenex, Torrance, CA, USA)Column Temperature: 30.0 ± 0.2°CMobile Phase: Acetonitrile and 0.05 M potassium dihydrogen phosphate solution (pH = 2.9, adjusted with 85% orthophosphoric acid) in a 35:65 ratioMode: IsocraticFlow Rate: 1.0 mL/minDetection Wavelength: 230 nmThe set contains data in LCD/ LCB format, created using the LabSolutions software (HPLC, Nexera LC 2040C). Data file (.lcd) contains all analysis results and acquisition information from the following files. Data in .txt format can be read without the need for LabSolutions software.
DOI: 10.5281/zenodo.10648335
title: Source data from: Xiaoxia Yi, Grégoire Vincent, Tianyu Hu, Jianli Liu, James Lutz, Haibao Ren, Lei Chen, David F. R. P. Burslem, Joseph D. Birch, Min Cao, James W. Dalling, David A. Coomes, Géraldine Derroire, Hu Du, Shuai Fang, Guangze Jin, Jinbo Li, Fei Lin, Hongwei Ni, Michael J. O'Brien, Guochun Shen, Xihua Wang, Xingyu Wang, Jie Yang, Fuping Zeng, Daoguang Zhu,Yan Zhu, Yanjun Su, Qinghua Guo, Keping Ma, Xiangcheng Mi. Canopy structural diversity modulates the effect of climate on primary productivity in forests.

description: This dataset includes species diversity, canopy structural diversity, forest productivity, topographic variables, climatic variables from 16 forest dynamics plots:



The species diversity and forest productivity data were calculated from ground census data;

The canopy structural diversity was calculated from airborne laser scanning data;

 Topographic variables were calculated from elevational data of each plot;

Climatic variables were downloaded from WorldClim using the center coordinates of each plot.
DOI: 10.5281/zenodo.15074883
title: Source data from: Xiaoxia Yi, Grégoire Vincent, Tianyu Hu, Jianli Liu, James Lutz, Haibao Ren, Lei Chen, David F. R. P. Burslem, Joseph D. Birch, Min Cao, James W. Dalling, David A. Coomes, Géraldine Derroire, Hu Du, Shuai Fang, Guangze Jin, Jinbo Li, Fei Lin, Hongwei Ni, Michael J. O'Brien, Guochun Shen, Xihua Wang, Xingyu Wang, Jie Yang, Fuping Zeng, Daoguang Zhu,Yan Zhu, Yanjun Su, Qinghua Guo, Keping Ma, Xiangcheng Mi. Canopy structural diversity modulates the effect of climate on primary productivity in forests.

description: This dataset includes species diversity, canopy structural diversity, forest productivity, topographic variables, climatic variables from 16 forest dynamics plots:



The species diversity and forest productivity data were calculated from ground census data;

The canopy structural diversity was calculated from airborne laser scanning data;

 Topographic variables were calculated from elevational data of each plot;

Climatic variables were downloaded from WorldClim using the center coordinates of each plot.
DOI: 10.5281/zenodo.12792998
title: INASEQ

description: Nombre d'entretiens réalisés par région et par profession - 2024/07/12

Grille d'entretien biologiste

Grille d'entretien prescripteur
DOI: 10.5281/zenodo.12792997
title: INASEQ

description: Nombre d'entretiens réalisés par région et par profession 

Grille d'entretien biologiste

Grille d'entretien prescripteur
DOI: 10.5281/zenodo.15074901
title: INASEQ

description: Nombre d'entretiens réalisés par région et par profession 

Grille d'entretien biologiste

Grille d'entretien prescripteur
DOI: 10.15468/dl.fywuw7
title: Occurrence Download

description: A dataset containing 293 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((30.5106 -29.77031,31.03306 -29.77031,31.03306 -29.09727,30.5106 -29.09727,30.5106 -29.77031))",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 293 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024443-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.3354401
title: GRTSmh_base4frac: the raster data source GRTSmaster_habitats converted to base 4 fractions

description: The data source file is a monolayered GeoTIFF in the FLT8S datatype. In GRTSmh_base4frac, the decimal (i.e. base 10) integer values from the raster data source GRTSmaster_habitats (link) have been converted into base 4 fractions, using a precision of 13 digits behind the decimal mark (as needed to cope with the range of values). For example, the integer 16 (= 4^2) has been converted into 0.0000000000100 and 4^12 has been converted into 0.1000000000000.


Long base 4 fractions seem to be handled and stored easier than long (base 4) integers. This approach follows the one of Stevens & Olsen (2004) to represent the reverse hierarchical order in a GRTS sample as base-4-fraction addresses.


See R-code in the GitHub repository 'n2khab-preprocessing' at commit ecadaf5 for the creation from the GRTSmaster_habitats data source.


A reading function to return the data source in a standardized way into the R environment is provided by the R-package n2khab.


Beware that not all GRTS ranking numbers are present in the data source, as the original GRTS raster has been clipped with the Flemish outer borders (i.e., not excluding the Brussels Capital Region).
DOI: 10.5281/zenodo.3354402
title: GRTSmh_base4frac: the raster data source GRTSmaster_habitats converted to base 4 fractions

description: The data source file is a monolayered GeoTIFF in the FLT8S datatype. In GRTSmh_base4frac, the decimal (i.e. base 10) integer values from the raster data source GRTSmaster_habitats (link) have been converted into base 4 fractions, using a precision of 13 digits behind the decimal mark (as needed to cope with the range of values). For example, the integer 16 (= 4^2) has been converted into 0.0000000000100 and 4^12 has been converted into 0.1000000000000.


Long base 4 fractions seem to be handled and stored easier than long (base 4) integers. This approach follows the one of Stevens & Olsen (2004) to represent the reverse hierarchical order in a GRTS sample as base-4-fraction addresses.


See R-code in the GitHub repository 'n2khab-preprocessing' at commit ecadaf5 for the creation from the GRTSmaster_habitats data source.


A reading function to return the data source in a standardized way into the R environment is provided by the R-package n2khab.


Beware that not all GRTS ranking numbers are present in the data source, as the original GRTS raster has been clipped with the Flemish outer borders (i.e., not excluding the Brussels Capital Region).
DOI: 10.5281/zenodo.3354403
title: GRTSmh_brick: the raster data source GRTSmaster_habitats converted to 10 hierarchical cell address levels at the original resolution

description: The data source file is a 10-layered GeoTIFF file, derived from the raster data source GRTSmaster_habitats (link). Both GeoTIFFs (GRTSmaster_habitats, GRTSmh_brick) use the INT4S datatype. The GRTSmh_brick data source (resolution 32 m) holds the decimal integer ranking numbers of 10 hierarchical levels of the GRTS cell addresses, including the one from GRTSmaster_habitats (with GRTS cell addresses at the resolution level).


See R-code in the GitHub repository 'n2khab-preprocessing' at commit ecadaf5 for its creation from the GRTSmaster_habitats data source.


A reading function to return the data source in a standardized way into the R environment is provided by the R-package n2khab.


The higher-level ranking numbers of the RasterBrick allow spatially balanced samples at lower spatial resolution than that of 32 m, and can also be used for aggregation purposes. The provided hierarchical levels correspond to the resolutions vector 32 * 2^(0:9) (minimum: 32 meters, maximum: 16384 meters).


Beware that not all GRTS ranking numbers are present in the data source, as the original GRTS raster has been clipped with the Flemish outer borders (i.e., not excluding the Brussels Capital Region).
DOI: 10.5281/zenodo.3354404
title: GRTSmh_brick: the raster data source GRTSmaster_habitats converted to 10 hierarchical cell address levels at the original resolution

description: The data source file is a 10-layered GeoTIFF file, derived from the raster data source GRTSmaster_habitats (link). Both GeoTIFFs (GRTSmaster_habitats, GRTSmh_brick) use the INT4S datatype. The GRTSmh_brick data source (resolution 32 m) holds the decimal integer ranking numbers of 10 hierarchical levels of the GRTS cell addresses, including the one from GRTSmaster_habitats (with GRTS cell addresses at the resolution level).


See R-code in the GitHub repository 'n2khab-preprocessing' at commit ecadaf5 for its creation from the GRTSmaster_habitats data source.


A reading function to return the data source in a standardized way into the R environment is provided by the R-package n2khab.


The higher-level ranking numbers of the RasterBrick allow spatially balanced samples at lower spatial resolution than that of 32 m, and can also be used for aggregation purposes. The provided hierarchical levels correspond to the resolutions vector 32 * 2^(0:9) (minimum: 32 meters, maximum: 16384 meters).


Beware that not all GRTS ranking numbers are present in the data source, as the original GRTS raster has been clipped with the Flemish outer borders (i.e., not excluding the Brussels Capital Region).
DOI: 10.5281/zenodo.3354405
title: GRTSmh_diffres: the raster data source GRTSmaster_habitats converted to 9 hierarchical cell address levels at the corresponding lower resolution

description: The GRTSmh_diffres data source file is a file collection, composed of nine monolayered GeoTIFF files of the INT4S datatype plus a GeoPackage with six polygon layers:



	

	
The polygon layers in the GeoPackage are the dissolved, polygonized versions of levels 4 to 9 of the GRTSmh_brick data source (link). This means that they provide the decimal (i.e. base 10) integer values of these higher hierarchical levels of the GRTS cell addresses of the raw data source GRTSmaster_habitats (link). Hence, the polygons are typically squares that correspond to the GRTS cell at the specified hierarchical level. The polygon layer is however restricted to the non-NA cells of the original GRTSmaster_habitats raster. Consequently, a part of the polygons is clipped along the Flemish border. Levels 1 to 3 are not provided for the whole of Flanders, because this would inflate the GPKG file. You can look at the source code to do such things.
	
	

	
The GeoTIFF files provide the respective levels 1 to 9 of the GRTSmh_brick data source in a raster format, at the resolution that corresponds to the GRTS cell at the specified hierarchical level. The presence of NA cells around Flanders at level 0 implies that, with decreasing resolution, the raster's extent increases and larger areas outside Flanders are covered by non-NA cells along the border.
	



The higher-level ranking numbers (compared to the original level 0) allow spatially balanced samples at lower spatial resolution than that of 32 m, and can also be used for aggregation purposes.


See R-code in the GitHub repository 'n2khab-preprocessing' at commit ecadaf5 for the creation from the GRTSmh_brick data source.


A reading function to return the data source in a standardized way into the R environment is provided by the R-package n2khab.


Beware that not all GRTS ranking numbers at the specified level are provided, as the original GRTS raster has been clipped with the Flemish outer borders (i.e., not excluding the Brussels Capital Region).
DOI: 10.5281/zenodo.3354406
title: GRTSmh_diffres: the raster data source GRTSmaster_habitats converted to 9 hierarchical cell address levels at the corresponding lower resolution

description: The GRTSmh_diffres data source file is a file collection, composed of nine monolayered GeoTIFF files of the INT4S datatype plus a GeoPackage with six polygon layers:



	

	
The polygon layers in the GeoPackage are the dissolved, polygonized versions of levels 4 to 9 of the GRTSmh_brick data source (link). This means that they provide the decimal (i.e. base 10) integer values of these higher hierarchical levels of the GRTS cell addresses of the raw data source GRTSmaster_habitats (link). Hence, the polygons are typically squares that correspond to the GRTS cell at the specified hierarchical level. The polygon layer is however restricted to the non-NA cells of the original GRTSmaster_habitats raster. Consequently, a part of the polygons is clipped along the Flemish border. Levels 1 to 3 are not provided for the whole of Flanders, because this would inflate the GPKG file. You can look at the source code to do such things.
	
	

	
The GeoTIFF files provide the respective levels 1 to 9 of the GRTSmh_brick data source in a raster format, at the resolution that corresponds to the GRTS cell at the specified hierarchical level. The presence of NA cells around Flanders at level 0 implies that, with decreasing resolution, the raster's extent increases and larger areas outside Flanders are covered by non-NA cells along the border.
	



The higher-level ranking numbers (compared to the original level 0) allow spatially balanced samples at lower spatial resolution than that of 32 m, and can also be used for aggregation purposes.


See R-code in the GitHub repository 'n2khab-preprocessing' at commit ecadaf5 for the creation from the GRTSmh_brick data source.


A reading function to return the data source in a standardized way into the R environment is provided by the R-package n2khab.


Beware that not all GRTS ranking numbers at the specified level are provided, as the original GRTS raster has been clipped with the Flemish outer borders (i.e., not excluding the Brussels Capital Region).
DOI: 10.15468/dl.zkp3k9
title: Occurrence Download

description: A dataset containing 8651 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Alnus rubra Bong., Alnus rubra Desf., Alnus rubra Desf. ex Corrie, Alnus rubra Desf. ex Steud.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8651 records from 135 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024444-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jfz43r
title: Occurrence Download

description: A dataset containing 4080 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "PublishingOrg is one of (618f0fdc-3f11-49dd-9375-0d9686c8aefe, 54a7048f-6d1f-468e-bd38-a585e05ca24d, 315127e0-d7bb-11db-9885-b8a03c50a862, f6b48504-1651-4a49-a88d-c2bc6178694d, bc092ff0-02e4-11dc-991f-b8a03c50a862, b3bf3a83-1f68-4541-a03f-330d30d567f5, 396d5f30-dea9-11db-8ab4-b8a03c50a862, dfad10f6-d84b-4fa2-b6d0-df2a3eb38b65, e88c96a3-5884-4e51-a580-e417ca4c9eed)",
 "TaxonKey is Bivalvia"
 ]
}

 The dataset includes 4080 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024445-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sp37kx
title: Occurrence Download

description: A dataset containing 160190 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cuculus canorus Linnaeus, 1758",
 "Continent is Europe",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1981",
 "Year is less than or equal to 2005"
 ]
}

 The dataset includes 160190 records from 463 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024426-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.58132/b2bvpx
title: Lasy porolne i stare w polskich Karpatach Wschodnich - baza danych o roślinności, glebie i środowisku geograficznym z 294 powierzchni badawczych

description: Załączony plik zawiera dane z 294 powierzchni badawczych zlokalizowanych w lasach starych i porolnych (powstałych po wysiedleniach lat 40. XX wieku) polskich Karpat Wschodnich. Podczas badań terenowych, w 2020 roku, wykonano zdjęcia fitosocjologiczne, pobrano próbki glebowe oraz wykonano zdjęcia hemisferyczne. Do każdej powierzchni badawczej przyporządkowano także dane dotyczące ukształtowania terenu obliczone z Numerycznego Modelu Terenu. Szczegółowe informacje dotyczące pobierania danych w terenie opisane są w powiązanych publikacjach.
DOI: 10.15468/dl.5r7s5b
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((3.83030 44.67329,4.01359 44.67329,4.01359 44.74658,3.83030 44.74658,3.83030 44.67329))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aegolius funereus (Linnaeus, 1758)"
 ]
}

 The dataset's 1 records were derived from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024435-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.waty9v
title: Occurrence Download

description: A dataset containing 351 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Megapodius nicobariensis Blyth, 1846"
 ]
}

 The dataset includes 351 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024446-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mra287
title: Occurrence Download

description: A dataset containing 3120 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Andira inermis (W.Wright) DC., Andira inermis Kunth)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3120 records from 240 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024447-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a97g8t
title: Occurrence Download

description: A dataset containing 160 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is China",
 "Geometry POLYGON((-21.23149 3.42157,144.23149 3.42157,144.23149 69.57843,-21.23149 69.57843,-21.23149 3.42157))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tamiops swinhoei (Milne-Edwards, 1874)"
 ]
}

 The dataset includes 160 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024449-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5522/04/28604234
title: Synthetic dataset of 100 fundus auto fluorescence of inherited retinal disease

description: Description of the data and file structureSynthetic dataset containing 100 Fundus Auto Fluorescence (FAF) images from each of 10 genes which includes (ABCA4, BEST1, EFEMP1, EYS, MYO7A, PRPH2, RPGR, RS1, TIMP3 and USH2A). These images were generated by the SynthEye algorithm (https://www.ophthalmologyscience.org/article/S2666-9145(22)00147-6/fulltext).Files and variablesFile: syntheye100_synthetic_faf.zip<b>Description:</b> Each foldercorresponds to a gene name (ABCA4, BEST1, EFEMP1, EYS, MYO7A, PRPH2, RPGR, RS1, TIMP3 and USH2A). Each folder contains 100 synthetic Fundus Auto Fluorescence images generated by the SynthEye algorithm (https://www.ophthalmologyscience.org/article/S2666-9145(22)00147-6/fulltext).Code/softwareNo software is needed to view the data. The images were generated by SynthEye (https://www.ophthalmologyscience.org/article/S2666-9145(22)00147-6/fulltext). The code base for SynthEye can be found here: https://github.com/pontikos-lab/syntheyeHuman subjects dataThis data is synthetic data. It is therefore not identifiable.
DOI: 10.15468/dl.er3bch
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((3.83030 44.67329,4.01359 44.67329,4.01359 44.74658,3.83030 44.74658,3.83030 44.67329))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aegolius funereus (Linnaeus, 1758)"
 ]
}

 The dataset includes 19 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024450-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3qjz9x
title: Occurrence Download

description: A dataset containing 172907 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Quercus rubra L."
 ]
}

 The dataset includes 172907 records from 1173 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024419-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s8ppj4
title: Occurrence Download

description: A dataset containing 41830855 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Germany"
 ]
}

 The dataset includes 41830855 records from 3119 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0150687-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.lln8zj
title: Occurrence Download

description: A dataset containing 1769 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Agnes Marion Ayre Herbarium (NFLD)"
 ]
}

 The dataset includes 1769 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017485-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gfzrn6
title: Occurrence Download

description: A dataset containing 486 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Tigridia pavonia (L.f.) Redouté"
 ]
}

 The dataset includes 486 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003789-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zshfpv
title: Occurrence Download

description: A dataset containing 2505643 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "HasCoordinate is true",
 "TaxonKey is Aves",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2505643 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017485-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.