cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0182718.10fu
title: SH0182718.10FU

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/sh0182719.10fu
title: SH0182719.10FU

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/sh0182720.10fu
title: SH0182720.10FU

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/sh0182721.10fu
title: SH0182721.10FU

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/sh0182722.10fu
title: SH0182722.10FU

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/sh0182723.10fu
title: SH0182723.10FU

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/sh0182724.10fu
title: SH0182724.10FU

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/sh0182725.10fu
title: SH0182725.10FU

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/sh0182726.10fu
title: SH0182726.10FU

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/sh0182727.10fu
title: SH0182727.10FU

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/q2fsq2
title: Données naturalistes opportunistes issues de la plateforme INaturalist-Données naturalistes opportunistes "julianeguiraud"

description: Données naturalistes opportunistes saisies sur iNaturalist à partir du compte "julianeguiraud"
DOI: 10.5281/zenodo.16950414
title: Open Data by Martinus Nathanael for Mobile Health Application UX Research in Indonesia
DOI: 10.15468/dl.z576tj
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Insecta)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-165 22.5,-157.5 22.5,-157.5 30,-165 30,-165 22.5))"
 ]
}

 The dataset includes 61 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041731-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.14955.87845
title: 5th Light Infantry Firing Squad Condemned identified by relatives
DOI: 10.18168/agrav.m.fg5.216
title: Observations made with meter FG5-216

description: Observations made with meter FG5-216
DOI: 10.18168/agrav.m.fg5.218
title: Observations made with meter FG5-218

description: Observations made with meter FG5-218
DOI: 10.18168/agrav.m.fg5x.216
title: Observations made with meter FG5X-216

description: Observations made with meter FG5X-216
DOI: 10.18168/agrav.m.fg5x.302
title: Observations made with meter FG5X-302

description: Observations made with meter FG5X-302
DOI: 10.15468/dl.kn79dk
title: Occurrence Download

description: A dataset containing 88782 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Odontites vernus (Bellardi) Dumort.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 88782 records from 671 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015410-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15187274
title: Data to support  "An Integrated Modelling Framework to Assess Subsidence from Coal Seam Gas Depressurisation"

description: The data repository is created to support a paper titled "An Integrated Modelling Framework to Assess Subsidence from Coal Seam Gas Depressurisation" submitted to Water Resources Research. The model calibration datasets including groundwater levels, InSAR and water production are included in the repository.
DOI: 10.5281/zenodo.15187275
title: Data to support  "An Integrated Modelling Framework to Assess Subsidence from Coal Seam Gas Depressurisation"

description: The data repository is created to support a paper titled "An Integrated Modelling Framework to Assess Subsidence from Coal Seam Gas Depressurisation" submitted to Water Resources Research. The model calibration datasets including groundwater levels, InSAR and water production are included in the repository.
DOI: 10.15468/dl.qrvedz
title: Occurrence Download

description: A dataset containing 95889 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Illinois Natural History Survey - Mollusk Collection"
 ]
}

 The dataset includes 95889 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015420-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5yf2ya
title: Occurrence Download

description: A dataset containing 13527 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is CWS: Waterbird colony database (Atlantic region)"
 ]
}

 The dataset includes 13527 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015425-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ybkb58
title: Occurrence Download

description: A dataset containing 104948 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Halyomorpha halys (Stål, 1855)"
 ]
}

 The dataset includes 104948 records from 355 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015422-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6kqksg
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "TaxonKey is Marmota marmota (Linnaeus, 1758)"
 ]
 },
 "HasCoordinate is TRUE",
 "Year is greater than or equal to 2010",
 "Year is less than or equal to 2024",
 "DecimalLatitude is greater than or equal to 36.285692670554845",
 "DecimalLatitude is less than or equal to 45.40012245958927",
 "DecimalLongitude is greater than or equal to 9.253608205317772",
 "DecimalLongitude is less than or equal to 19.089499639948606",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018254-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ygxxdy
title: Occurrence Download

description: A dataset listing the 367 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-82.833 8.56823,-82.75519 8.56823,-82.75519 8.66291,-82.833 8.66291,-82.833 8.56823))",
 "HasGeospatialIssue is false",
 "TaxonKey is Chordata"
 ]
}

 The dataset's 367 records were derived from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018250-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nyhcxw
title: Occurrence Download

description: A dataset containing 739 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Dipsastraea speciosa (Dana, 1846)"
 ]
}

 The dataset includes 739 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018255-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dcxayr
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ptychoglossus myersi Harris, 1994"
 ]
}

 The dataset includes 31 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018256-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14230550
title: Public Participation in the EU National Energy and Climate Plans

description: Overview

This record contains data on the quality of the public participation processes that were used in the development of the European Union National Energy and Climate Plans (NECPs). Reports submitted between 2018 and 2023 (n=81) were coded using an analytical framework with three main dimensions: inclusiveness, robustness, and integration into policymaking.

File descriptions

necp_participation_readme.docx – an overview of the Zenodo record and the files it contains.

necp_participation_codebook.pdf – a detailed codebook describing the analytical framework, its sub-components (dimensions and indicators), the codes provided for each indicator, and the scores attached to each code.  

necp_participation_data.xlsx – an Excel workbook containing the full dataset, formatted for general accessibility. This file is further sub-divided into five worksheets.



Overview: a brief description of the main components of the Excel workbook.

Data Dictionary: provides descriptions of each label used in the dataset, including contextual information, coding data, and participation quality scores.

Codes: dataset of the individual codes that were assigned for each participation indicator, organised by country and report type.

Scores: dataset of the participation quality scores for each report, based on the results of the qualitative coding.

Full Dataset: the full dataset containing contextual information, qualitative codes, and scores. This sheet is a formatted version of the CSV version of the dataset (see below).


necp_participation_data.csv – the full dataset on participation quality related to the NECPs, including contextual information, coding results, and scores for each report.

necp_supplemental_tables.pdf – contains tables included as supplemental material for the Journal of European Article reporting on this analysis (see full Zenodo record for up-to-date information).

Suggested data citation

von Homeyer, Ingmar, Sebastian Oberthür, Lea Schewe, Oda G. Flekkøy, and Brendan Moore (2024). Dataset: Public participation in the National Energy and Climate Plans (v1.0). Zenodo. https://doi.org/10.5281/zenodo.14230551.
DOI: 10.5281/zenodo.14230551
title: Public Participation in the EU National Energy and Climate Plans

description: Overview

This record contains data on the quality of the public participation processes that were used in the development of the European Union National Energy and Climate Plans (NECPs). Reports submitted between 2018 and 2023 (n=81) were coded using an analytical framework with three main dimensions: inclusiveness, robustness, and integration into policymaking.

File descriptions

necp_participation_readme.docx – an overview of the Zenodo record and the files it contains.

necp_participation_codebook.pdf – a detailed codebook describing the analytical framework, its sub-components (dimensions and indicators), the codes provided for each indicator, and the scores attached to each code.  

necp_participation_data.xlsx – an Excel workbook containing the full dataset, formatted for general accessibility. This file is further sub-divided into five worksheets.



Overview: a brief description of the main components of the Excel workbook.

Data Dictionary: provides descriptions of each label used in the dataset, including contextual information, coding data, and participation quality scores.

Codes: dataset of the individual codes that were assigned for each participation indicator, organised by country and report type.

Scores: dataset of the participation quality scores for each report, based on the results of the qualitative coding.

Full Dataset: the full dataset containing contextual information, qualitative codes, and scores. This sheet is a formatted version of the CSV version of the dataset (see below).


necp_participation_data.csv – the full dataset on participation quality related to the NECPs, including contextual information, coding results, and scores for each report.

necp_supplemental_tables.pdf – contains tables included as supplemental material for the Journal of European Article reporting on this analysis (see full Zenodo record for up-to-date information).

Suggested data citation

von Homeyer, Ingmar, Sebastian Oberthür, Lea Schewe, Oda G. Flekkøy, and Brendan Moore (2024). Dataset: Public participation in the National Energy and Climate Plans (v1.0). Zenodo. https://doi.org/10.5281/zenodo.14230551.
DOI: 10.15468/dl.xr5esu
title: Occurrence Download

description: A dataset containing 208 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Habenaria cornuta Lindl."
 ]
}

 The dataset includes 208 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018257-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.