cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.a8a7g2
title: Occurrence Download

description: A dataset containing 1106386 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (France, Luxembourg, Netherlands, Germany, Belgium)",
 "OccurrenceStatus is Present",
 "TaxonKey is Salmo trutta Linnaeus, 1758",
 "Year 2000-2025"
 ]
}

 The dataset includes 1106386 records from 322 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015110-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ek7hr3
title: Occurrence Download

description: A dataset containing 38651 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (November, December)",
 "OccurrenceStatus is Present",
 "TaxonKey is Larus canus Linnaeus, 1758",
 "Year 2010-2013"
 ]
}

 The dataset includes 38651 records from 144 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061529-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25383/city.26519890.v1
title: <b>Dyadic Person Similarity Predicts Similarity in Face Judgments</b>

description: Here we share our data and code for our project <b>Dyadic Person Similarity Predicts Similarity in Face Judgments.</b>Research shows that perceivers consistently extract information from faces to judge whether others are attractive, trustworthy, or dominant. However, there is also substantial variability among perceivers when making these social judgements. We seem to use our own dispositions as frameworks for making judgements about others, so could it be that two people who are similar in their dispositions also tend to make more similar social judgements? A consistent understanding of others may serve as a foundation for our social relationships, be it platonic or romantic. The present study investigated whether dyadic similarities in participants’ own dispositions are related to similarities in their social face judgements. 307 participants based in the UK rated 24 faces on six social traits. Participants also rated themselves on 13 social traits and completed a 60-item personality questionnaire. We computed dissimilarities between pairs of participants for face judgements, self-perceived trait ratings, and personality ratings, resulting in three separate dissimilarity matrices. Each entry in each matrix depicted pairwise distances in ratings between participants. Using representational similarity analysis, the three matrices were then correlated with each other. Results showed that both the self-perceived trait and personality matrices were significantly correlated with the face judgement matrix respectively. These results indicate that participants with more similar personalities and social trait dispositions were more likely to make similar social face judgements. Importantly, these associations were stable even when controlling for age, gender, ethnicity, and geographical location<i>. </i>These findings show that people who are more similar to each other also perceive the world in a similar manner and may form the basis for how we gravitate towards others, build connections and form relationships.The study was approved by the Psychology Research Ethics Committee at City, University of London.We pre-registered our study, specifying sample size, inclusion, and exclusion criteria (https://doi.org/10.17605/OSF.IO/ZR92G).Here we share the raw anonymised data and the code we used for main analyses. The README file explains the folder contents, including what each script does. Raw data consists of csv files for each participant. Code runs in MATLAB.<br>
DOI: 10.15468/dl.n77773
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((147.978733 -34.83512, 147.978733 -34.837366, 147.98547 -34.837366, 147.98547 -34.83512, 147.978733 -34.83512))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061534-240626123714530/datasets/export for details.
DOI: 10.15468/dl.7p8fpp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.942181 -34.83512, 148.942181 -34.837366, 148.944426 -34.837366, 148.944426 -34.83512, 148.942181 -34.83512))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061535-240626123714530/datasets/export for details.
DOI: 10.15468/dl.fsu6yh
title: Occurrence Download

description: A dataset containing 298121 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aegypius monachus (Linnaeus, 1766)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 298121 records from 214 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061528-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tuf85j
title: Occurrence Download

description: A dataset containing 129 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.7715 -34.814908, 148.7715 -34.8194, 148.767008 -34.8194, 148.767008 -34.821645, 148.7715 -34.821645, 148.7715 -34.830629, 148.773746 -34.830629, 148.773746 -34.814908, 148.7715 -34.814908)), ((148.773746 -34.830629, 148.773746 -34.846349, 148.775991 -34.846349, 148.775991 -34.844103, 148.780483 -34.844103, 148.780483 -34.837366, 148.775991 -34.837366, 148.775991 -34.830629, 148.773746 -34.830629)), ((148.775991 -34.846349, 148.775991 -34.850841, 148.780483 -34.850841, 148.780483 -34.846349, 148.775991 -34.846349)), ((148.780483 -34.850841, 148.780483 -34.853087, 148.782729 -34.853087, 148.782729 -34.850841, 148.780483 -34.850841)), ((148.780483 -34.846349, 148.782729 -34.846349, 148.782729 -34.844103, 148.780483 -34.844103, 148.780483 -34.846349)))"
 ]
}

 The dataset includes 129 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061536-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tyqbmz
title: Occurrence Download

description: A dataset containing 108595 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Denmark",
 "GadmGid is DNK.3_1",
 "Geometry POLYGON((10.2 56.972,10.4 56.972,10.4 57.1,10.2 57.1,10.2 56.972))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 108595 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061531-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.av897u
title: Occurrence Download

description: A dataset containing 600 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Especies de peces registradas en las sub-cuencas hidrográficas de la jurisdicción de Corpochivor (Boyacá-Colombia)"
 ]
}

 The dataset includes 600 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061537-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u22muf
title: Occurrence Download

description: A dataset containing 4762 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (April, May, June)",
 "TaxonKey is Chroicocephalus brunnicephalus (Jerdon, 1840)",
 "Year 2007-2024"
 ]
}

 The dataset includes 4762 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061538-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.suynjf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.142676 -34.83512, 148.147168 -34.83512, 148.147168 -34.837366, 148.144922 -34.837366, 148.144922 -34.841858, 148.147168 -34.841858, 148.147168 -34.844103, 148.153905 -34.844103, 148.153905 -34.841858, 148.158397 -34.841858, 148.158397 -34.837366, 148.151659 -34.837366, 148.151659 -34.83512, 148.158397 -34.83512, 148.158397 -34.830629, 148.160642 -34.830629, 148.160642 -34.828383, 148.151659 -34.828383, 148.151659 -34.830629, 148.144922 -34.830629, 148.144922 -34.828383, 148.142676 -34.828383, 148.142676 -34.83512)), ((148.142676 -34.83512, 148.135939 -34.83512, 148.135939 -34.837366, 148.142676 -34.837366, 148.142676 -34.83512)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061539-240626123714530/datasets/export for details.
DOI: 10.15468/dl.3ywrgw
title: Occurrence Download

description: A dataset containing 6183 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (April, May, June)",
 "OccurrenceStatus is Present",
 "TaxonKey is Larus belcheri Vigors, 1829",
 "Year 1998-2024"
 ]
}

 The dataset includes 6183 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061540-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bcw9z5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.737813 -34.83512, 148.737813 -34.837366, 148.742304 -34.837366, 148.742304 -34.841858, 148.74455 -34.841858, 148.74455 -34.837366, 148.749042 -34.837366, 148.749042 -34.83512, 148.737813 -34.83512))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061541-240626123714530/datasets/export for details.
DOI: 10.15468/dl.4cyk3c
title: Occurrence Download

description: A dataset containing 24441 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (January, November, December)",
 "TaxonKey is Chroicocephalus brunnicephalus (Jerdon, 1840)",
 "Year 2007-2024"
 ]
}

 The dataset includes 24441 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061542-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dd.9jzxfb
title: Atlantic sea-urchins

description: Data downloaded through the "rgbif" package. No processing was done, but the data was aggregated to produce the files.
DOI: 10.15468/dl.wndwjs
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.755779 -34.830629, 148.755779 -34.83512, 148.751288 -34.83512, 148.751288 -34.837366, 148.758025 -34.837366, 148.758025 -34.841858, 148.760271 -34.841858, 148.760271 -34.844103, 148.758025 -34.844103, 148.758025 -34.850841, 148.767008 -34.850841, 148.767008 -34.846349, 148.7715 -34.846349, 148.7715 -34.844103, 148.764762 -34.844103, 148.764762 -34.837366, 148.760271 -34.837366, 148.760271 -34.83512, 148.758025 -34.83512, 148.758025 -34.830629, 148.755779 -34.830629))"
 ]
}

 The dataset includes 18 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061544-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nven64
title: Occurrence Download

description: A dataset containing 27976 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (April, May, June)",
 "OccurrenceStatus is Present",
 "TaxonKey is Ichthyaetus audouinii (Payraudeau, 1826)",
 "Year 2002-2022"
 ]
}

 The dataset includes 27976 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061545-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ny9cmt
title: Occurrence Download

description: A dataset containing 7719 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (January, November, December)",
 "OccurrenceStatus is Present",
 "TaxonKey is Larus belcheri Vigors, 1829",
 "Year 1998-2024"
 ]
}

 The dataset includes 7719 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061546-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xy7ykk
title: Occurrence Download

description: A dataset containing 361501 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Papilio machaon Linnaeus, 1758"
 ]
}

 The dataset includes 361501 records from 2918 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061523-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0180204.10fu
title: SH0180204.10FU

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/sh0180205.10fu
title: SH0180205.10FU

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/sh0180206.10fu
title: SH0180206.10FU

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/sh0180207.10fu
title: SH0180207.10FU

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/sh0180208.10fu
title: SH0180208.10FU

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/sh0180209.10fu
title: SH0180209.10FU

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/sh0180210.10fu
title: SH0180210.10FU

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/sh0180211.10fu
title: SH0180211.10FU

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/sh0180212.10fu
title: SH0180212.10FU

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.