cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0172873.10fu
title: SH0172873.10FU

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/sh0172874.10fu
title: SH0172874.10FU

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/sh0172875.10fu
title: SH0172875.10FU

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/sh0172876.10fu
title: SH0172876.10FU

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/sh0172877.10fu
title: SH0172877.10FU

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/sh0172878.10fu
title: SH0172878.10FU

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.g2enef
title: Occurrence Download

description: A dataset containing 57001 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lynx lynx (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than or equal to 1980"
 ]
}

 The dataset includes 57001 records from 103 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004329-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15296032
title: Validation of the ALARO1-SFX regional climate model over Belgium across different resolutions

description: This dataset accompanies the publication "Validation of the ALARO1-SFX regional climate model over Belgium across different resolutions". The data are derived from simulations with the ALARO1-SFX model, performed for the period 1992–2022 at three horizontal resolutions: 25 km, 12 km, and 4 km. For each simulation, the following data are provided:



Monthly averaged precipitation, regridded over Belgium.

Monthly averaged near-surface temperature, regridded over Belgium.

Hourly precipitation time series for Uccle, Belgium.

Annual maximum precipitation values for event durations of 1, 2, 3, 6, 12, 24, 48, and 72 hours, for three topographic regions in Belgium: Low-Belgium, Middle-Belgium, and High-Belgium.


Further details regarding the data generation and processing methods are available in the accompanying publication.
DOI: 10.5281/zenodo.10637097
title: Ultra-high scale cytometry-based cellular interaction mapping - Data repository
DOI: 10.5281/zenodo.10694407
title: Ultra-high scale cytometry-based cellular interaction mapping - Data repository and analysis workflow
DOI: 10.5281/zenodo.10869760
title: Ultra-high scale cytometry-based cellular interaction mapping - Data repository and analysis workflow
DOI: 10.5281/zenodo.10869976
title: Ultra-high scale cytometry-based cellular interaction mapping - Data repository and analysis workflow
DOI: 10.5281/zenodo.10870739
title: Ultra-high scale cytometry-based cellular interaction mapping - Data repository and analysis workflow
DOI: 10.5281/zenodo.13774409
title: Ultra-high scale cytometry-based cellular interaction mapping - Data repository

description: This is the repository for datasets used in Vonficht, Jopp-Saile, Yousefian, Flore et al. Ultra-high scale cytometry-based cellular interaction mapping, Nature Methods (2025). Associated analysis code can be found at https://github.com/agSHaas/ultra-high-scale-cytometry-based-cellular-interaction-mapping, and the repository for the accompanying R package is hosted at https://github.com/agSHaas/PICtR.
DOI: 10.5281/zenodo.14671510
title: Ultra-high scale cytometry-based cellular interaction mapping - Data repository

description: This is the repository for datasets used in Vonficht, Jopp-Saile, Yousefian, Flore et al. Ultra-high scale cytometry-based cellular interaction mapping, Nature Methods (2025). Associated analysis code can be found at https://github.com/agSHaas/ultra-high-scale-cytometry-based-cellular-interaction-mapping, and the repository for the accompanying R package is hosted at https://github.com/agSHaas/PICtR.
DOI: 10.5281/zenodo.15301963
title: Robustness of brain state identification in synthetic phase-coupled neurodynamics using Hidden Markov Models

description: This repository contains the synthetic data generated for the paper "Robustness of brain state identification in synthetic phase-coupled neurodynamics using Hidden Markov Models" published in Frontiers in System Neuroscience.

Each file contains the timecourse of the signals used to generate a particular coupling.

Citation: Pieramico G, Makkinayeri S, Guidotti R, Basti A, Voso D, Lucarelli D, D’Andrea A, L’Abbate T, Romani GL, Pizzella V and Marzetti L (2025) Robustness of brain state identification in synthetic phase-coupled neurodynamics using Hidden Markov Models. Front. Syst. Neurosci. 19:1548437. doi: 10.3389/fnsys.2025.1548437
DOI: 10.5281/zenodo.15301964
title: Robustness of brain state identification in synthetic phase-coupled neurodynamics using Hidden Markov Models

description: This repository contains the synthetic data generated for the paper "Robustness of brain state identification in synthetic phase-coupled neurodynamics using Hidden Markov Models" published in Frontiers in System Neuroscience.

Each file contains the timecourse of the signals used to generate a particular coupling.

Citation: Pieramico G, Makkinayeri S, Guidotti R, Basti A, Voso D, Lucarelli D, D’Andrea A, L’Abbate T, Romani GL, Pizzella V and Marzetti L (2025) Robustness of brain state identification in synthetic phase-coupled neurodynamics using Hidden Markov Models. Front. Syst. Neurosci. 19:1548437. doi: 10.3389/fnsys.2025.1548437
DOI: 10.5281/zenodo.11067674
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Germany

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.  

The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. 

Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below:  



Commission Regulation (EU) 625/2017, on the application of food and feed law

Commission Delegated Regulation (EU) 2022/931

Commission Implementing Regulation (EU) 2022/932

Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006


These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). 

More details are available in last year's finalised call for data ‘Call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA (europa.eu)’.

REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: 

OCC-CHEMMON2020 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2021 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2022 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2023 – Federal Office of Consumer Protection and Food Safety
description: DE; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.15302112
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Germany

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.  

The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. 

Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below:  



Commission Regulation (EU) 625/2017, on the application of food and feed law

Commission Delegated Regulation (EU) 2022/931

Commission Implementing Regulation (EU) 2022/932

Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006


These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). 

More details are available in last year's finalised call for data ‘Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA’.

REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: 

OCC-CHEMMON2020 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2021 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2022 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2023 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2024 – Federal Office of Consumer Protection and Food Safety
description: DE; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.7034539
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Germany

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.  

The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. 

Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below:  



Commission Regulation (EU) 625/2017, on the application of food and feed law

Commission Delegated Regulation (EU) 2022/931

Commission Implementing Regulation (EU) 2022/932

Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006


These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). 

More details are available in last year's finalised call for data ‘Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA’.

REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: 

OCC-CHEMMON2020 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2021 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2022 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2023 – Federal Office of Consumer Protection and Food Safety

OCC-CHEMMON2024 – Federal Office of Consumer Protection and Food Safety
description: DE; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.7034540
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Germany

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: Commission Regulation (EU) 625/2017, on the application of food and feed law Commission Regulation (EC) 1881/2006, on maximum levels for certain contaminants in foodstuffs Commission Regulation (EC) 2017/2158 establishing mitigation measures and benchmark levels for the reduction of the presence of acrylamide in food These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2020, split by sampling year (data element ‘sampY’). More details are available in the ‘Call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA (europa.eu)’. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: OCC-CHEMMON2020 – Federal Office of Consumer Protection and Food Safety
description: DE; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.7038167
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Germany

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: Commission Regulation (EU) 625/2017, on the application of food and feed law Commission Regulation (EC) 1881/2006, on maximum levels for certain contaminants in foodstuffs Commission Regulation (EC) 2017/2158 establishing mitigation measures and benchmark levels for the reduction of the presence of acrylamide in food These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2021, split by sampling year (data element ‘sampY’). More details are available in the ‘Call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA (europa.eu)’. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: OCC-CHEMMON2020 – Federal Office of Consumer Protection and Food Safety OCC-CHEMMON2021 – Federal Office of Consumer Protection and Food Safety
description: DE; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.7808768
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Germany

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: Commission Regulation (EU) 625/2017, on the application of food and feed law Commission Regulation (EC) 1881/2006, on maximum levels for certain contaminants in foodstuffs Commission Regulation (EC) 2017/2158 establishing mitigation measures and benchmark levels for the reduction of the presence of acrylamide in food These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). More details are available in the ‘Call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA (europa.eu)’. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: OCC-CHEMMON2020 – Federal Office of Consumer Protection and Food Safety OCC-CHEMMON2021 – Federal Office of Consumer Protection and Food Safety OCC-CHEMMON2022 – Federal Office of Consumer Protection and Food Safety
description: DE; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.15239480
title: Complete Dataset #Girlhood Trend on TikTok

description: Complete dataset including content analysis and Multimodal Critical Discourse Analysis (MCDA) of the #girlhood content on TikTok.
DOI: 10.5281/zenodo.15239481
title: Complete Dataset #Girlhood Trend on TikTok

description: Complete dataset including content analysis and Multimodal Critical Discourse Analysis (MCDA) of the #girlhood content on TikTok.
DOI: 10.5281/zenodo.15284432
title: Health professionals' perceptions of climate change: Challenges, preparedness, and the role of health systems and human resources. A systematic review
DOI: 10.15468/dl.ej87v8
title: Occurrence Download

description: A dataset containing 2262 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Carcharhinus coatesi (Whitley, 1939)"
 ]
}

 The dataset includes 2262 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004337-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.