cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1106146.10fu
title: SH1106146.10FU

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: 10.15468/dl.ng6nnz
title: Occurrence Download

description: A dataset containing 1471658 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Madagascar"
 ]
}

 The dataset includes 1471658 records from 1114 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0146168-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tj85jt
title: Occurrence Download

description: A dataset containing 7365 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 Harpactes oreskios (Temminck, 1823)"
 ]
}

 The dataset includes 7365 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002412-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yfqa7o
title: Occurrence Download

description: A dataset containing 3420 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Alismataceae"
 ]
}

 The dataset includes 3420 records from 91 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049607-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5zxrhj
title: Occurrence Download

description: A dataset containing 109 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Rubus glaucus Benth."
 ]
}

 The dataset includes 109 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036922-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6yygvh
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Argyrolobium aegacanthoides (Vved.) Moteetee"
 ]
}

 The dataset includes 32 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015638-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9rvblh
title: Occurrence Download

description: A dataset containing 6710 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brachychiton populneus (Schott & Endl.) R.Br.",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 6710 records from 66 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049608-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6nfanx
title: Occurrence Download

description: A dataset containing 978 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Priodontes maximus (Kerr, 1792)"
 ]
}

 The dataset includes 978 records from 92 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043849-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.977cak
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Argentina",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Senecio helgae Cabrera"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094395-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dm9h3y
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arctotis gumbletonii Hook.fil."
 ]
}

 The dataset includes 23 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015657-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3fwxgf
title: Occurrence Download

description: A dataset containing 20312 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brachypodium distachyon (L.) P.Beauv.",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 20312 records from 135 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049609-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xmg4aj
title: Occurrence Download

description: A dataset containing 52101 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Upupa epops Linnaeus, 1758",
 "HasCoordinate is true",
 "Year 2013-2017",
 "Geometry POLYGON((-10 35.5,4.5 35.5,4.5 45,-10 45,-10 35.5))",
 {
 "or" : [
 {
 "not" : {
 "CoordinateUncertaintyInMeters" : [
 "is not null"
 ]
 }
 },
 "CoordinateUncertaintyInMeters is less than or equal to 250"
 ]
 }
 ]
}

 The dataset includes 52101 records from 100 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043801-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive102359.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive102359.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094448.10fu
title: SH0094448.10FU

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: 10.17632/2xrh39r68m
title: Firm attributes and business obstacles: Insights from probit regression of World Bank Enterprise Survey data

description: Research Overview and Hypotheses 
This repository contains the replication code and methodological documentation for our study examining the relationship between firm attributes (size, age, ownership structure, growth rate, and managerial experience) and the severity of business obstacles in Zambia. Grounded in Institutional Theory, the Resource-Based View (RBV), and Credit Rationing Theory, the research tests the hypothesis that firm characteristics differentiate how businesses perceive and experience business obstacles. The study posits that resource-constrained firms (e.g., SMEs or younger firms) are more likely to report higher severity in obstacles such as access to finance, corruption, and infrastructure deficits compared to their larger, established counterparts.
Data Description and Collection 
The underlying data is drawn from the 2019 World Bank Enterprise Survey (WBES) for Zambia. The dofile provides further details. First, Firm Attributes are constructed, recoding raw inputs into usable metrics for firm age (years), size (employee count categories), domestic ownership percentages, and historical growth rates. Second, Business Obstacles are derived from Likert-scale responses (ranging from 0="No Obstacle" to 4="Very Severe Obstacle"). The code further transforms these into binary variables to isolate "Major" and "Severe" constraints for probit analysis.
Notable Findings and Interpretation 
Descriptive analysis of the dataset reveals that the most critical hurdles facing Zambian enterprises are access to finance, electricity supply, competition from the informal sector, customs regulations, tax rates, corruption, and political instability. The regression outputs, which can be reproduced using the attached code, demonstrate that the burden of these obstacles is not uniformly distributed. The data shows that firm attributes act as significant predictors for the intensity of these constraints. For interpretation, the Ordinal and Binary Probit models reveal the marginal effects of specific characteristics; for instance, a positive coefficient for the "Domestic_ownership" variable regarding "Access to Finance" indicates that wholly locally owned firms are more likely to perceive finance as a severe barrier than firms with some foreign ownership. 
Usage and Replication 
This repository provides the complete Stata syntax required to clean the raw data, generate descriptive statistics, and execute the regression models presented in the published article. Users should interpret the output tables as evidence of the varying influence of firm demographics on business operations. To use this code, users must download the raw dataset (Zambia-2019-full data.dta) from the World Bank Enterprise Surveys portal, as licensing restrictions prevent redistribution of the data here. The code is annotated to guide the user through recoding variables, generating the horizontal bar chart, and producing the tables for both ordinal and binary probit regressions.
DOI: 10.13145/bacdive102360.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive102360.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094449.10fu
title: SH0094449.10FU

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: 10.13145/bacdive102361.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094450.10fu
title: SH0094450.10FU

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: 10.17632/2xrh39r68m.1
title: Firm attributes and business obstacles: Insights from probit regression of World Bank Enterprise Survey data

description: Research Overview and Hypotheses 
This repository contains the replication code and methodological documentation for our study examining the relationship between firm attributes (size, age, ownership structure, growth rate, and managerial experience) and the severity of business obstacles in Zambia. Grounded in Institutional Theory, the Resource-Based View (RBV), and Credit Rationing Theory, the research tests the hypothesis that firm characteristics differentiate how businesses perceive and experience business obstacles. The study posits that resource-constrained firms (e.g., SMEs or younger firms) are more likely to report higher severity in obstacles such as access to finance, corruption, and infrastructure deficits compared to their larger, established counterparts.
Data Description and Collection 
The underlying data is drawn from the 2019 World Bank Enterprise Survey (WBES) for Zambia. The dofile provides further details. First, Firm Attributes are constructed, recoding raw inputs into usable metrics for firm age (years), size (employee count categories), domestic ownership percentages, and historical growth rates. Second, Business Obstacles are derived from Likert-scale responses (ranging from 0="No Obstacle" to 4="Very Severe Obstacle"). The code further transforms these into binary variables to isolate "Major" and "Severe" constraints for probit analysis.
Notable Findings and Interpretation 
Descriptive analysis of the dataset reveals that the most critical hurdles facing Zambian enterprises are access to finance, electricity supply, competition from the informal sector, customs regulations, tax rates, corruption, and political instability. The regression outputs, which can be reproduced using the attached code, demonstrate that the burden of these obstacles is not uniformly distributed. The data shows that firm attributes act as significant predictors for the intensity of these constraints. For interpretation, the Ordinal and Binary Probit models reveal the marginal effects of specific characteristics; for instance, a positive coefficient for the "Domestic_ownership" variable regarding "Access to Finance" indicates that wholly locally owned firms are more likely to perceive finance as a severe barrier than firms with some foreign ownership. 
Usage and Replication 
This repository provides the complete Stata syntax required to clean the raw data, generate descriptive statistics, and execute the regression models presented in the published article. Users should interpret the output tables as evidence of the varying influence of firm demographics on business operations. To use this code, users must download the raw dataset (Zambia-2019-full data.dta) from the World Bank Enterprise Surveys portal, as licensing restrictions prevent redistribution of the data here. The code is annotated to guide the user through recoding variables, generating the horizontal bar chart, and producing the tables for both ordinal and binary probit regressions.
DOI: 10.13145/bacdive102361.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive102362.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094451.10fu
title: SH0094451.10FU

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: 10.13145/bacdive102362.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive102363.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094452.10fu
title: SH0094452.10FU

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: 10.17632/3gc7gw5dwt
title: Progression of joint damages in a colony of dogs with naturally occurring osteoarthritis: Results of an original 36-month longitudinal study

description: This longitudinal imaging study describes the natural progression of computed radiographic (CR) joint damages in a cohort of dogs with hindlimb osteoarthritis and their relationship with MRI findings. Fifty-one OA dogs and six controls were followed over three years using standardized radiographic and MRI scoring. Distinct progression trajectories (fast, slow, and non-progressors) were identified, with the stifle joint showing the clearest differentiation. Fast-progressors exhibited greater structural deterioration and stronger alignment between clinical impairment, radiographic damage, and MRI lesions. These findings highlight the heterogeneous nature of canine OA progression and the clinical relevance of repeated imaging.
DOI: 10.13145/bacdive102363.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive102364.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094453.10fu
title: SH0094453.10FU

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: 10.13145/bacdive102364.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive102365.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.