cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.4jsjy7
title: Occurrence Download

description: A dataset containing 281 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Arthropoda",
 "DatasetKey is Plan régional d'actions en faveur des odonates (PRAO) : 4ème phase (2019 - 2020) menée par le CEN Nouvelle-Aquitaine-Observations faunistiques fortuites réalisées par le CEN Nouvelle-Aquitaine (Étude Leucorrhines)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-25.03991 31.75, 41.65954 31.75, 41.65954 71.53037, -25.03991 71.53037, -25.03991 31.75))"
 ]
}

 The dataset includes 281 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0217805-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n8t5cf
title: Occurrence Download

description: A dataset containing 841678 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Spondyliosoma cantharus (Linnaeus, 1758), Acanthopagrus latus (Houttuyn, 1782), Epinephelus moara (Temminck & Schlegel, 1842), Epinephelus coioides (Hamilton, 1822), Thunnus thynnus (Linnaeus, 1758), Thunnus maccoyii (Castelnau, 1872), Thunnus albacares (Bonnaterre, 1788), Scomber scombrus Linnaeus, 1758, Scomber japonicus Houttuyn, 1782, Sarda sarda (Bloch, 1793), Rastrelliger kanagurta (Cuvier, 1816), Katsuwonus pelamis (Linnaeus, 1758), Sander lucioperca (Linnaeus, 1758), Lepidonotothen nudifrons (Lönnberg, 1905), Dissostichus eleginoides Smitt, 1898, Pseudupeneus prayensis (Cuvier, 1829), Morone saxatilis (Walbaum, 1792), Dicentrarchus labrax (Linnaeus, 1758), Myripristis murdjan (Forsskål, 1775), Lutjanus argentimaculatus (Forsskål, 1775), Lates calcarifer (Bloch, 1790), Coryphaena hippurus Linnaeus, 1758, Oreochromis niloticus (Linnaeus, 1758), Oreochromis mossambicus (Peters, 1852), Neolamprologus brichardi (Poll, 1974), Micropterus salmoides (Lacepède, 1802), Trachurus japonicus (Temminck & Schlegel, 1844), Parambassis ranga (Hamilton, 1822))"
 ]
}

 The dataset includes 841678 records from 985 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028958-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xp22w6
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Senecio productus I.Thomps."
 ]
}

 The dataset includes 45 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0124346-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p4qa5r
title: Occurrence Download

description: A dataset containing 34143 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "DatasetKey is EOD – eBird Observation Dataset",
 "GadmGid is GBR",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Alcedo atthis (Linnaeus, 1758)",
 "Year 2013-2023"
 ]
}

 The dataset includes 34143 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0227565-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zwzvcc
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Fuirena bidgoodiae Hoenselaar & Muasya"
 ]
}

 The dataset includes 7 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0221087-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.84v2t9
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Arthropoda",
 "DatasetKey is Diagnostic écologique et élaboration d'une notice de gestion (prairies humides et calcaires) sur la commune de Monflanquin (47) menés entre 2017 et 2022 par le CEN Nouvelle-Aquitaine-Observations faunistiques fortuites réalisées par le CEN Nouvelle-Aquitaine",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-25.03991 31.75, 41.65954 31.75, 41.65954 71.53037, -25.03991 71.53037, -25.03991 31.75))"
 ]
}

 The dataset includes 33 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0217809-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y92dmh
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Senecio pottsii Armstr."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0124331-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6qzcet
title: Occurrence Download

description: A dataset containing 4025969 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 1980-2023"
 ]
}

 The dataset includes 4025969 records from 2222 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0218281-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60586/snt447.nvbk.798
title: RNAseq (with probes) data from the lung (left) of a 55 year-old white male
DOI: 10.60586/snt934.thbx.456
title: RNAseq (with probes) data from the lung (right) of a 58 year-old white male
DOI: 10.15468/dl.nb4rzf
title: Occurrence Download

description: A dataset containing 49126 species occurrences available in GBIF matching the query:
{
 "and" : [
 "MediaType is Image",
 "TaxonKey is one of (Myotis bechsteinii, Barbastella barbastellus, Spalax microphthalmus, Allactaga sibirica, Spermophilus brevicauda, Meriones tamariscinus, Ondatra zibethicus, Eptesicus nilssonii)"
 ]
}

 The dataset includes 49126 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018632-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7ugfq6
title: Occurrence Download

description: A dataset containing 289 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Gladiolus scullyi)"
 ]
}

 The dataset includes 289 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018634-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xn4ew9
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Monoplacophora)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-180 -50,-170 -50,-170 -40,-180 -40,-180 -50))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018635-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11583/dtu.29665346
title: DTU PV plant - Drone Infrared Thermography Dataset: Influence of Irradiance and Altitude

description: Dataset containing IRT images, electroluminescence images and IV curves.This dataset has been collected as part of the SOLARIS project and is presented in the publication: "<i>Advancing Drone Infrared Thermography for Photovoltaic Plant Inspections Defect Detection: Influence of Altitude and Environmental Conditions</i>".This dataset collects all the measurements related to the publication; IRT images from a drone of DTU's PV plant at Riso. Four altitudes and irradiacnes were collected for each of the modules under study. Furthermore, the dataset contains IV curves and EL images of each module as a reference. Details about the measurement setup are provided in the manuscript. AttachmentsThe ZIP is organized by defect type. Each defect folder contains a folder per module.Inside the module folder an EL image of the module can be found.File type: .NEFFilename: Module#_EL_Defect_ExposureTimeThe soiling folders contain visible images of the module instead.For each module an IRT folder contains all the IRT images of such module under different irradiances and drone altitudes.File type: .png for visualization.Filetype: .raw for image processing, raw file containing the image in temperature values. Converted from the camera radiometric .jpeg.raw files are all sampled to 363x605 pixels and can be loaded as float32 in python.Each module folder contains its IV curve:File type .csv with measured voltage and current.The IV curve is an average of 3 measurements at STC conditions.Soiling modules IV:2 modules were IV measured in the field with a portabel IV tracer (Soiling 1 Mod 1 and Soiling 2 Mod 2).<br>
DOI: 10.11583/dtu.29665346.v1
title: DTU PV plant - Drone Infrared Thermography Dataset: Influence of Irradiance and Altitude

description: Dataset containing IRT images, electroluminescence images and IV curves.This dataset has been collected as part of the SOLARIS project and is presented in the publication: "<i>Advancing Drone Infrared Thermography for Photovoltaic Plant Inspections Defect Detection: Influence of Altitude and Environmental Conditions</i>".This dataset collects all the measurements related to the publication; IRT images from a drone of DTU's PV plant at Riso. Four altitudes and irradiacnes were collected for each of the modules under study. Furthermore, the dataset contains IV curves and EL images of each module as a reference. Details about the measurement setup are provided in the manuscript. AttachmentsThe ZIP is organized by defect type. Each defect folder contains a folder per module.Inside the module folder an EL image of the module can be found.File type: .NEFFilename: Module#_EL_Defect_ExposureTimeThe soiling folders contain visible images of the module instead.For each module an IRT folder contains all the IRT images of such module under different irradiances and drone altitudes.File type: .png for visualization.Filetype: .raw for image processing, raw file containing the image in temperature values. Converted from the camera radiometric .jpeg.raw files are all sampled to 363x605 pixels and can be loaded as float32 in python.Each module folder contains its IV curve:File type .csv with measured voltage and current.The IV curve is an average of 3 measurements at STC conditions.Soiling modules IV:2 modules were IV measured in the field with a portabel IV tracer (Soiling 1 Mod 1 and Soiling 2 Mod 2).<br>
DOI: 10.15468/dl.kd56pc
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cephalostachyum scandens"
 ]
}

 The dataset includes 19 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0077870-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9fw6c8
title: Occurrence Download

description: A dataset containing 1138 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Imperata cylindrica",
 "HasCoordinate is TRUE",
 "Country is Korea, Republic of"
 ]
}

 The dataset includes 1138 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0077868-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1406435.10fu
title: SH1406435.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.11587/l33o5l
title: Microcensus Labour Force Survey / Housing Survey 2018 (SUF edition)

description: Full edition for scientific use. With about 20,000 households surveyed per quarter, the Microcensus is the largest regularly conducted sample survey in Austria. It is an important data source for central national and international labour market indicators and regularly provides information on housing and families. The survey is also known as the Microcensus Labour Force Survey (MZ-AKE), as the labour market-related questions are surveyed according to international guidelines (according to the ILO - International Labour Organisation) and the Austrian part is the so-called European Labour Force Survey (LFS).
description: Mikrocensus
description: To access the data, please download the Terms of Use Agreement for Microcensus Data by Statistics Austria, sign it and send it to info@aussda.at.
DOI: 10.11587/xge7tf
title: Microcensus Labour Force Survey / Housing Survey 2019 (SUF edition)

description: Full edition for scientific use. With about 20,000 households surveyed per quarter, the Microcensus is the largest regularly conducted sample survey in Austria. It is an important data source for central national and international labour market indicators and regularly provides information on housing and families. The survey is also known as the Microcensus Labour Force Survey (MZ-AKE), as the labour market-related questions are surveyed according to international guidelines (according to the ILO - International Labour Organisation) and the Austrian part is the so-called European Labour Force Survey (LFS).
description: Mikrocensus
description: To access the data, please download the Terms of Use Agreement for Microcensus Data by Statistics Austria, sign it and send it to info@aussda.at.
DOI: 10.11587/znvvcs
title: Microcensus 2003, 4. quarter: Standard Survey (SUF edition)

description: Full edition for scientific use. Since 1983 labour force surveys (LFS) are conducted annually in all European Union (EU) member states. The LFS serve as a basis for internationally compatible (in terms of definition and survey method) data on employment and unemployment for the European Commission. In Austria the LFS is conducted fully annually. Central questions for the assessment of the number of employed and unemployed persons (and as a result for the calculation of the unemployment rate according to international standards) are in addition (since 1994) asked quarterly in the Microcensus standard survey. In Austria (as well as in several other states) the LFS is only conducted among the population in private households; people who live in institutions (retirement homes, boarding homes, and the like) are not included in the survey (the Microcensus special surveys are not conducted in institutional households due to organisational problems and problems with performing the surveys there). Because of a major reform of the Labour Force Survey the special survey program isn’t available 4.quarter 2003.
description: Microcensus
description: To access the data, please download the Terms of Use Agreement for Microcensus Data by Statistics Austria, sign it and send it to info@aussda.at.
DOI: 10.11587/zoobke
title: Editing EU-SILC UDB Longitudinal Data for Differential Mortality Analyses. SAS code and documentation.

description: This SAS code extracts data from EU-SILC User Database (UDB) longitudinal files and edits it such that a file is produced that can be further used for differential mortality analyses. Information from the original D, R, H and P files is merged per person and possibly pooled over several longitudinal data releases. Vital status information is extracted from target variables DB110 and RB110, and time at risk between the first interview and either death or censoring is estimated based on quarterly date information.

Apart from path specifications, the SAS code consists of several SAS macros. Two of them require parameter specification from the user. The other ones are just executed. The code was written in Base SAS, Version 9.4.

By default, the output file contains several variables which are necessary for differential mortality analyses, such as sex, age, country, year of first interview, and vital status information. In addition, the user may specify the analytical variables by which mortality risk should be compared later, for example educational level or occupational class. These analytical variables may be measured either at the first interview (the baseline) or at the last interview of a respondent. The output file is available in SAS format and by default also in csv format.
DOI: 10.15156/bio/sh1406436.10fu
title: SH1406436.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1406437.10fu
title: SH1406437.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1406439.10fu
title: SH1406439.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1406440.10fu
title: SH1406440.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.18231878
title: Importância dos recursos hídricos de Angola para o desenvolvimento económico social e ambiental com enfoque na província do Huambo
DOI: 10.5281/zenodo.18231879
title: Importância dos recursos hídricos de Angola para o desenvolvimento económico social e ambiental com enfoque na província do Huambo