cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0216209.10fu
title: SH0216209.10FU

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/sh0216210.10fu
title: SH0216210.10FU

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/sh0216211.10fu
title: SH0216211.10FU

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/sh0216212.10fu
title: SH0216212.10FU

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/sh0216213.10fu
title: SH0216213.10FU

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/sh0216214.10fu
title: SH0216214.10FU

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.n965xh
title: Occurrence Download

description: A dataset containing 362636 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 },
 "TaxonKey is Spilosoma lubricipeda (Linnaeus, 1758)"
 ]
}

 The dataset includes 362636 records from 636 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003319-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e219961
title: FHFA Data: Uniform Appraisal Dataset Aggregate Statistics

description: The Uniform Appraisal Dataset (UAD) Aggregate Statistics Data File and Dashboards are the nation’s first publicly available datasets of aggregate statistics on appraisal records, giving the public new access to a broad set of data points and trends found in appraisal reports. The UAD Aggregate Statistics for Enterprise Single-Family, Enterprise Condominium, and Federal Housing Administration (FHA) Single-Family appraisals may be grouped by neighborhood characteristics, property characteristics and different geographic levels.DocumentationOverview (10/28/2024)Data Dictionary (10/28/2024)Data File Version History and Suppression Rates (12/18/2024)Dashboard Guide (2/3/2025)UAD Aggregate Statistics DashboardsThe UAD Aggregate Statistics Dashboards are the visual front end of the UAD Aggregate Statistics Data File. The Dashboards are designed to provide easy access to customized maps and charts for all levels of users. Access the UAD Aggregate Statistics Dashboards here.UAD Aggregate Statistics DatasetsNotes:Some of the data files are relatively large in size and will not open correctly in certain software packages, such as Microsoft Excel. All the files can be opened and used in data analytics software such as SAS, Python, or R.All CSV files are zipped.<br><br>
description: Smallest Geographic Unit: census tract
DOI: 10.3886/e219961v1
title: FHFA Data: Uniform Appraisal Dataset Aggregate Statistics

description: The Uniform Appraisal Dataset (UAD) Aggregate Statistics Data File and Dashboards are the nation’s first publicly available datasets of aggregate statistics on appraisal records, giving the public new access to a broad set of data points and trends found in appraisal reports. The UAD Aggregate Statistics for Enterprise Single-Family, Enterprise Condominium, and Federal Housing Administration (FHA) Single-Family appraisals may be grouped by neighborhood characteristics, property characteristics and different geographic levels.DocumentationOverview (10/28/2024)Data Dictionary (10/28/2024)Data File Version History and Suppression Rates (12/18/2024)Dashboard Guide (2/3/2025)UAD Aggregate Statistics DashboardsThe UAD Aggregate Statistics Dashboards are the visual front end of the UAD Aggregate Statistics Data File. The Dashboards are designed to provide easy access to customized maps and charts for all levels of users. Access the UAD Aggregate Statistics Dashboards here.UAD Aggregate Statistics DatasetsNotes:Some of the data files are relatively large in size and will not open correctly in certain software packages, such as Microsoft Excel. All the files can be opened and used in data analytics software such as SAS, Python, or R.All CSV files are zipped.<br><br>
description: Smallest Geographic Unit: census tract
DOI: 10.15468/dl.wrxrbv
title: Occurrence Download

description: A dataset containing 11517 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 },
 "TaxonKey is Eutolmus rufibarbis (Meigen, 1820)"
 ]
}

 The dataset includes 11517 records from 75 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003343-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14918857
title: AMPERE Summary Plot Movies (2022-Oct)

description: 2022-Oct AMPERE summary plot movies. See included zenodo_summary_plot_movie_description document for details.
DOI: 10.5281/zenodo.14918858
title: AMPERE Summary Plot Movies (2022-Oct)

description: 2022-Oct AMPERE summary plot movies. See included zenodo_summary_plot_movie_description document for details.
DOI: 10.15468/dl.mmwz9x
title: Occurrence Download

description: A dataset containing 15625 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "OccurrenceStatus is Present",
 "TaxonKey is Araneus diadematus Clerck, 1757"
 ]
}

 The dataset includes 15625 records from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003341-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wj6699
title: Occurrence Download

description: A dataset containing 3203 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "Country is one of (India, Hong Kong, Nepal, China, Viet Nam, Myanmar, Bangladesh, Pakistan, Thailand)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is Coordinate rounded",
 "TaxonKey is Macaca mulatta (Zimmermann, 1780)",
 "Year 1780-2025"
 ]
}

 The dataset includes 3203 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003342-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14887997
title: Raw data of Mix_et_al_2025

description: Raw experimental data of Mix_et_al (2025) Nature Microbiology
DOI: 10.3886/e220583
title: FHFA Data: Uniform Appraisal Dataset (UAD) Appraisal-Level Public Use File (PUF)

description: Version 2.1 (2/4/2025)The Uniform Appraisal Dataset (UAD) Appraisal-Level Public Use File (PUF) is the nation’s first publicly available appraisal-level dataset of appraisal records, giving the public new access to a selected set of data fields found in appraisal reports. The UAD Appraisal-Level PUF are provided separately for the Enterprises (Fannie Mae and Freddie Mac) and Federal Housing Administration (FHA) appraisals:The Enterprise UAD Appraisal-Level PUF is based on a five percent nationally representative random sample of appraisals for single-family mortgages acquired by the Enterprises. The current release includes appraisals from 2013 through 2022.The FHA UAD Appraisal-Level PUF is based on a five percent nationally representative random sample of appraisals for single-family mortgages insured by FHA. The current release includes appraisals from 2017 through 2022.The UAD Appraisal-Level PUF is a resource for users capable of using statistical software to extract and analyze data. Users can download annual or combined files in CSV, R, SAS and Stata formats. All files are zipped for ease with download.The UAD Appraisal-Level PUF provides the public and policymakers with meaningful data about appraisals to identify trends, conduct research, and promote compliance. Public, transparent data about appraisals promotes a liquid, efficient, competitive, and resilient national housing market.​DocumentationUAD PUF Dat​a Dictionary Version 2.1 (2/4/2025)UAD PUF Version History Version 2.1 (2/4/2025)UAD PUF D​ata Documentation (2/4/2025)
description: appraisal level data
DOI: 10.3886/e220583v1
title: FHFA Data: Uniform Appraisal Dataset (UAD) Appraisal-Level Public Use File (PUF)

description: Version 2.1 (2/4/2025)The Uniform Appraisal Dataset (UAD) Appraisal-Level Public Use File (PUF) is the nation’s first publicly available appraisal-level dataset of appraisal records, giving the public new access to a selected set of data fields found in appraisal reports. The UAD Appraisal-Level PUF are provided separately for the Enterprises (Fannie Mae and Freddie Mac) and Federal Housing Administration (FHA) appraisals:The Enterprise UAD Appraisal-Level PUF is based on a five percent nationally representative random sample of appraisals for single-family mortgages acquired by the Enterprises. The current release includes appraisals from 2013 through 2022.The FHA UAD Appraisal-Level PUF is based on a five percent nationally representative random sample of appraisals for single-family mortgages insured by FHA. The current release includes appraisals from 2017 through 2022.The UAD Appraisal-Level PUF is a resource for users capable of using statistical software to extract and analyze data. Users can download annual or combined files in CSV, R, SAS and Stata formats. All files are zipped for ease with download.The UAD Appraisal-Level PUF provides the public and policymakers with meaningful data about appraisals to identify trends, conduct research, and promote compliance. Public, transparent data about appraisals promotes a liquid, efficient, competitive, and resilient national housing market.​DocumentationUAD PUF Dat​a Dictionary Version 2.1 (2/4/2025)UAD PUF Version History Version 2.1 (2/4/2025)UAD PUF D​ata Documentation (2/4/2025)
description: appraisal level data
DOI: 10.6084/m9.figshare.28473819
title: Biplots for the correlation matrix

description: The visualization of the correlation matrix by means of biplots is considered. The classical centering operations, either by the overall mean, the column means, or row and column means are shown to be problematic for the visualisation of the correlation matrix, and sub-optimal in terms of goodness-of-fit. More flexible adjustments are possible by using a single scalar adjustment, a set of column scalars or both row–and–column scalars using a weighted alternating least squares algorithm. Recently, correlation biplots with a single scalar adjustment have been advocated and outperform the usual correlation biplots made by principal component analysis. This article presents an iterative algorithm for a column adjustment of the correlation matrix with the goal of improving the goodness-of-fit over the the use of a single scalar adjustment and studies its usefulness in practical data analysis. The resulting biplots are harder to read but can be made more interpretable by using correlation tally sticks. Correlation tally sticks are advocated for improving the visualization of correlation structure. The weighted root mean squared error is used to compare low-dimensional approximations to the correlation matrix across methods.
DOI: 10.6084/m9.figshare.28473819.v1
title: Biplots for the correlation matrix

description: The visualization of the correlation matrix by means of biplots is considered. The classical centering operations, either by the overall mean, the column means, or row and column means are shown to be problematic for the visualisation of the correlation matrix, and sub-optimal in terms of goodness-of-fit. More flexible adjustments are possible by using a single scalar adjustment, a set of column scalars or both row–and–column scalars using a weighted alternating least squares algorithm. Recently, correlation biplots with a single scalar adjustment have been advocated and outperform the usual correlation biplots made by principal component analysis. This article presents an iterative algorithm for a column adjustment of the correlation matrix with the goal of improving the goodness-of-fit over the the use of a single scalar adjustment and studies its usefulness in practical data analysis. The resulting biplots are harder to read but can be made more interpretable by using correlation tally sticks. Correlation tally sticks are advocated for improving the visualization of correlation structure. The weighted root mean squared error is used to compare low-dimensional approximations to the correlation matrix across methods.
DOI: 10.15468/dl.rgpazh
title: Occurrence Download

description: A dataset containing 2700 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cenostigma pyramidale (Tul.) Gagnon & G.P.Lewis"
 ]
}

 The dataset includes 2700 records from 128 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003346-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8nnnwe
title: Occurrence Download

description: A dataset containing 991 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 },
 "TaxonKey is Thecophora atra (Fabricius, 1775)"
 ]
}

 The dataset includes 991 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003349-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nrm74f
title: Occurrence Download

description: A dataset containing 3283 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Drosophila suzukii (Matsumura, 1931)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 3283 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003301-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6juk7y
title: Occurrence Download

description: A dataset containing 239020 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Amanita muscaria (L.) Lam."
 ]
}

 The dataset includes 239020 records from 503 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003278-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xcg42x
title: Occurrence Download

description: A dataset containing 547162 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Ilex aquifolium L."
 ]
}

 The dataset includes 547162 records from 2193 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003333-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j5ukbn
title: Occurrence Download

description: A dataset containing 8619 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Echinoidea"
 ]
}

 The dataset includes 8619 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005258-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/8uatog
title: Senchal Mahananda Corridor

description: This is a list of seed plants (Angiosperms and gymnosperms) recorded from Senchal Mahananda Corridor.
DOI: 10.15468/biip6l
title: Seed Plants of Senchal Wildlife Sanctuary

description: This is a list of seed plants (angiosperms and gymnosperms) of the Senchal Wildlife Sanctuary in India.
DOI: 10.15468/xr8mrm
title: Seed Plants of Barsey Rhododendron Sanctuary

description: This is a list of seed plants (angiosperms and gymnosperms) recorded from the Barsey Rhododendron Sanctauary, India.
DOI: 10.15468/pad6kw
title: Seed Plants of Singhalila National Park

description: This is a list of seed plants (angiosperms and gymnosperms)recorded from the Singhalila National Park in India.
DOI: 10.15468/dl.69zwv4
title: Occurrence Download

description: A dataset containing 8101 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Oryx Blainville, 1816"
 ]
}

 The dataset includes 8101 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069957-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/independent-c69-42225
title: Claims (GX 14638 - GX 15135), 1988

description: Collection of claims filed against the LAPD with regards ranging from wrongful death to violation of civil rights, etc., 1988. PART OF A SERIES: The series includes materials related to the work product of Price Waterhouse, whose staff investigated citizen complaints and civil litigation claims involving the LAPD. Included are claims reports, claims analyses, card files, and arbitration reports; summaries of 83 selected civil litigation cases; materials from the personnel files of LAPD officers named in these cases, as well as documents listing their subsequent penalties; and statistics that break complaints down according to a variety of criteria, including race, gender, and police division.