cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18503004
title: Data for: Divergent Institutional Logics of Quantification in Research Evaluation

description: This dataset contains the institutional texts, coded data, and analysis codeused in the study:

“Divergent Institutional Logics of Quantification in Research Evaluation:Evidence from RPT Policies in Chinese and U.S. Research Universities”.

The dataset consists of four components:

(1) Original RPT policy documents from 100 research-intensive universities,including 50 institutions in China and 50 institutions in the United States.These documents include formal review, promotion, and tenure (RPT) policies,faculty appointment rules, and performance evaluation guidelines collectedfrom official university websites.

(2) A consolidated coded dataset (Excel/CSV) summarizing institutional designfeatures for all 100 universities. The table includes the following variables:

ID, Country, University, Authority Structure, Degree of Delegation,Outcome-based Threshold, Process-based Threshold, Performance Conversion,Peer Benchmarking.

Each row represents one university. Binary indicators (“Yes/No”) and ordinalscales are used to capture how quantification is institutionally embeddedwithin RPT regimes across the two national contexts.

(3) A Python script for statistical analysis and figure generation:    “analysis_and_visualization_RPT_quantification.py”.

This script reproduces the descriptive statistics, group comparisons, andfigures reported in the article.

All coding was conducted from the original policy texts. The dataset andaccompanying analysis code are intended to support transparency,replicability, and comparative research on research evaluation,quantification, and higher education governance.
DOI: 10.5281/zenodo.18503005
title: Data for: Divergent Institutional Logics of Quantification in Research Evaluation

description: This dataset contains the institutional texts, coded data, and analysis codeused in the study:

“Divergent Institutional Logics of Quantification in Research Evaluation:Evidence from RPT Policies in Chinese and U.S. Research Universities”.

The dataset consists of four components:

(1) Original RPT policy documents from 100 research-intensive universities,including 50 institutions in China and 50 institutions in the United States.These documents include formal review, promotion, and tenure (RPT) policies,faculty appointment rules, and performance evaluation guidelines collectedfrom official university websites.

(2) A consolidated coded dataset (Excel/CSV) summarizing institutional designfeatures for all 100 universities. The table includes the following variables:

ID, Country, University, Authority Structure, Degree of Delegation,Outcome-based Threshold, Process-based Threshold, Performance Conversion,Peer Benchmarking.

Each row represents one university. Binary indicators (“Yes/No”) and ordinalscales are used to capture how quantification is institutionally embeddedwithin RPT regimes across the two national contexts.

(3) A Python script for statistical analysis and figure generation:    “analysis_and_visualization_RPT_quantification.py”.

This script reproduces the descriptive statistics, group comparisons, andfigures reported in the article.

All coding was conducted from the original policy texts. The dataset andaccompanying analysis code are intended to support transparency,replicability, and comparative research on research evaluation,quantification, and higher education governance.
DOI: 10.15468/dl.qpy4w9
title: Occurrence Download

description: A dataset containing 6535372 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "HasCoordinate is true",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2019",
 "Geometry POLYGON((-25.0 54.0, 45.0 54.0, 45.0 59.0, -25.0 59.0, -25.0 54.0))"
 ]
}

 The dataset includes 6535372 records from 254 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016022-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bbxnsv
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cryptotis merriami Choate, 1970",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 39 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009894-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dsquf4
title: Occurrence Download

description: A dataset containing 394 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Agrostis breviculmis Hitchc."
 ]
}

 The dataset includes 394 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0279676-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g6zs88
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhodiola sachalinensis Boriss."
 ]
}

 The dataset includes 10 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0292674-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fhc93d
title: Occurrence Download

description: A dataset containing 37519 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dendragapus obscurus (Say, 1822)"
 ]
}

 The dataset includes 37519 records from 96 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051014-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x924pz
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is South Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pelargonium githagineum E.M.Marais"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0276293-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6q5npj
title: Occurrence Download

description: A dataset containing 5228 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-66.5332 49.34421,-85.04883 49.87576,-91.8457 46.92026,-90.79101 36.64491,-61.37695 37.11361,-58.91602 46.75993,-66.5332 49.34421))",
 "HasGeospatialIssue is false",
 "TaxonKey is Lonicera L."
 ]
}

 The dataset includes 5228 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037985-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h860es
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is Lachenalia reflexa Thunb.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 61 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009894-180730143533302/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u7ykat
title: Occurrence Download

description: A dataset containing 580 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Racomitrium lanuginosum (Hedw.) Brid.",
 "MediaType is Image",
 "BasisOfRecord is Human Observation"
 ]
}

 The dataset includes 580 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001843-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s6mebd
title: Occurrence Download

description: A dataset containing 538 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus lentiginosus var. borreganus M.E.Jones"
 ]
}

 The dataset includes 538 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0267781-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x9ms9y
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oenothera oakesiana (A.Gray) J.W.Robbins"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0288602-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.696waw
title: Occurrence Download

description: A dataset containing 123054 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Flora of Vladimir Oblast, Russia: an updated grid dataset (1867–2020)"
 ]
}

 The dataset includes 123054 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009894-180824113759888/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rzy9xf
title: Occurrence Download

description: A dataset containing 8457 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Microtus arvalis (Pallas, 1779)"
 ]
}

 The dataset includes 8457 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043675-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jmvdab
title: Occurrence Download

description: A dataset containing 695 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Thamnosma texana (A.Gray) Torr."
 ]
}

 The dataset includes 695 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002742-190307172214381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6yxw74
title: Occurrence Download

description: A dataset containing 4297741 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Ecuador"
 ]
}

 The dataset includes 4297741 records from 1153 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009894-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5h5qcc
title: Occurrence Download

description: A dataset containing 18768 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is PELD-ELPA Continuous monitoring of the micro and mesozooplankton of the Patos Lagoon estuary and adjacent coastal area"
 ]
}

 The dataset includes 18768 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0252209-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dx78hm
title: Occurrence Download

description: A dataset containing 80545 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Alces alces (Linnaeus, 1758)"
 ]
}

 The dataset includes 80545 records from 116 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0262252-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rq9r35
title: Occurrence Download

description: A dataset containing 12189 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oxalis dillenii Jacq."
 ]
}

 The dataset includes 12189 records from 268 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0288633-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18150/iyy5xu
title: Microwave-assisted hydrothermal synthesis of photocatalytic truncated-bipyramidal TiO2/Ti3CN heterostructures derived from Ti3CN MXene

description: This study explores a facile approach using a microwave-assisted hydrothermal method to synthesize a novel material with a unique architecture i.e., TiO2 decorating the surface of Ti3CN in the form of highly crystalline anatase truncated bipyramids with exposed {001} and {101} facets. The well-defined crystalline phase of TiO2 ensures low electron transfer resistance and minimizes the recombination of photogenerated electrons and holes at the TiO2/MXene interface, leading to a high photocatalytic performance.The dataset contains raw data of physicochemical, optoelectronics, and photocatalytic activity of truncated-bipyramidal TiO2/Ti3CN heterostructures derived from Ti3CN MXene.For more details, please refer to the README file.
DOI: 10.15156/bio/sh0158546.10fu
title: SH0158546.10FU

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/sh0158547.10fu
title: SH0158547.10FU

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/sh0158548.10fu
title: SH0158548.10FU

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/sh0158549.10fu
title: SH0158549.10FU

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/sh0158550.10fu
title: SH0158550.10FU

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/sh0158551.10fu
title: SH0158551.10FU

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/sh0158552.10fu
title: SH0158552.10FU

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/sh0158553.10fu
title: SH0158553.10FU

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.