cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.v8ff4t
title: Occurrence Download

description: A dataset containing 1112 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ameivula ocellifera (Spix, 1825)"
 ]
}

 The dataset includes 1112 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030710-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aghsjj
title: Occurrence Download

description: A dataset containing 91462 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Carcinus maenas (Linnaeus, 1758)"
 ]
}

 The dataset includes 91462 records from 337 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001655-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25403/upresearchdata.29064038
title: Processes involved in ASBVd pathogenesis using next-generation sequencing (NGS) to explore the host transcriptome in asymptomatic ASBVd-infected avocado

description: The aim of this work was to elucidate processes involved in ASBVd pathogenesis using next-generation sequencing (NGS) to explore the host transcriptome in asymptomatic ASBVd-infected avocado, as well as to investigate whether viroid-derived small RNAs (vd-sRNAs) produced from ASBVd can be implicated in the triggering of leaf chlorosis in symptomatic infections. The results signify the first recent exploration of the ASBVd-avocado interaction. Collectively, the results of our investigation start to shed light on the molecular mechanisms involved in ASBVd pathogenesis.
DOI: 10.25403/upresearchdata.29064038.v1
title: Processes involved in ASBVd pathogenesis using next-generation sequencing (NGS) to explore the host transcriptome in asymptomatic ASBVd-infected avocado

description: The aim of this work was to elucidate processes involved in ASBVd pathogenesis using next-generation sequencing (NGS) to explore the host transcriptome in asymptomatic ASBVd-infected avocado, as well as to investigate whether viroid-derived small RNAs (vd-sRNAs) produced from ASBVd can be implicated in the triggering of leaf chlorosis in symptomatic infections. The results signify the first recent exploration of the ASBVd-avocado interaction. Collectively, the results of our investigation start to shed light on the molecular mechanisms involved in ASBVd pathogenesis.
DOI: 10.5281/zenodo.3785005
title: Latvian results from the monitoring of pesticide residues in food

description: This dataset contains the analytical results of pesticide residues measured in the food products analysed by the national competent authorities. Pesticide residues resulting from the use of plant protection products on crops that are used for food or feed production may pose a risk factor for public health. For this reason, a comprehensive legislative framework has been established in the European Union (EU), which defines rules for the approval of active substances used in plant protection products, the use of plant protection products and for pesticide residues in food. In order to ensure a high level of consumer protection, legal limits, so called “maximum residue levels” or briefly “MRLs”, are established in Regulation (EC) No 396/2005. EU-harmonised MRLs are set for all pesticides covering all types of food products. A default MRL of 0.01 mg/kg is applicable for pesticides not explicitly mentioned in the MRL legislation. Regulation (EC) No 396/2005 imposes on Member States the obligation to carry out controls to ensure that food placed on the market is compliant with the legal limits. A sample is considered <strong>free of quantifiable residues</strong> if the analytes were not present in concentrations at or above the limit of quantification (LOQ). The LOQ is the smallest concentration of an analyte that can be quantified with the analytical method used to analyse the sample. It is commonly defined as the minimum concentration of the analyte in the test sample that can be determined with acceptable precision and accuracy. If a sample is <strong>contains quantifiable residues</strong> but within the legally permitted limit (maximum residue level, MRL), it is described as a sample with quantified residue levels within the legal limits (below or at the MRL) A sample is considered <strong>non-compliant</strong> with the legal limit (MRL), if the measured residue concentrations clearly exceed the legal limits, taking into account the measurement uncertainty. It is current practice that the uncertainty of the analytical measurement is taken into account before legal or administrative sanctions are imposed on food business operators for infringement of the MRL legislation. <strong>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION:</strong> MOPER_2018 - Institute of Food Safety, Animal Health and Environment MOPER_2017 - Institute of Food Safety, Animal Health and Environment MOPER_2016 - Institute of Food Safety, Animal Health and Environment MOPER_2015 - Institute of Food Safety, Animal Health and Environment MOPER_2014 - Institute of Food Safety, Animal Health and Environment MOPER_2013 - Institute of Food Safety, Animal Health and Environment MOPER_2012 - Institute of Food Safety, Animal Health and Environment MOPER_2011 - Institute of Food Safety, Animal Health and Environment <strong>We are seeking feedback on our open data please complete the survey at the link below:<br> https://ec.europa.eu/eusurvey/runner/9344dfa0-f384-cb72-65f6-6c187a6d0f14</strong>
description: LV; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.3260836
title: Latvian results from the monitoring of pesticide residues in food

description: This dataset contains the analytical results of pesticide residues measured in the food products analysed by the national competent authorities. Pesticide residues resulting from the use of plant protection products on crops that are used for food or feed production may pose a risk factor for public health. For this reason, a comprehensive legislative framework has been established in the European Union (EU), which defines rules for the approval of active substances used in plant protection products, the use of plant protection products and for pesticide residues in food. In order to ensure a high level of consumer protection, legal limits, so called “maximum residue levels” or briefly “MRLs”, are established in Regulation (EC) No 396/2005. EU-harmonised MRLs are set for all pesticides covering all types of food products. A default MRL of 0.01 mg/kg is applicable for pesticides not explicitly mentioned in the MRL legislation. Regulation (EC) No 396/2005 imposes on Member States the obligation to carry out controls to ensure that food placed on the market is compliant with the legal limits. A sample is considered <strong>free of quantifiable residues</strong> if the analytes were not present in concentrations at or above the limit of quantification (LOQ). The LOQ is the smallest concentration of an analyte that can be quantified with the analytical method used to analyse the sample. It is commonly defined as the minimum concentration of the analyte in the test sample that can be determined with acceptable precision and accuracy. If a sample is <strong>contains quantifiable residues</strong> but within the legally permitted limit (maximum residue level, MRL), it is described as a sample with quantified residue levels within the legal limits (below or at the MRL) A sample is considered <strong>non-compliant</strong> with the legal limit (MRL), if the measured residue concentrations clearly exceed the legal limits, taking into account the measurement uncertainty. It is current practice that the uncertainty of the analytical measurement is taken into account before legal or administrative sanctions are imposed on food business operators for infringement of the MRL legislation. <strong>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION:</strong> MOPER_2016 – Institute of Food Safety, Animal Health and Environment MOPER_2017 – Institute of Food Safety, Animal Health and Environment <strong>We are seeking feedback on our open data please complete the survey at the link below:<br> https://ec.europa.eu/eusurvey/runner/9344dfa0-f384-cb72-65f6-6c187a6d0f14</strong>
description: LV; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.1323594
title: Latvian Results From The Monitoring Of Pesticide Residues In Food

description: This dataset contains the analytical results of pesticide residues measured in the food products analysed by the national competent authorities. Pesticide residues resulting from the use of plant protection products on crops that are used for food or feed production may pose a risk factor for public health. For this reason, a comprehensive legislative framework has been established in the European Union (EU), which defines rules for the approval of active substances used in plant protection products, the use of plant protection products and for pesticide residues in food. In order to ensure a high level of consumer protection, legal limits, so called “maximum residue levels” or briefly “MRLs”, are established in Regulation (EC) No 396/2005. EU-harmonised MRLs are set for all pesticides covering all types of food products. A default MRL of 0.01 mg/kg is applicable for pesticides not explicitly mentioned in the MRL legislation. Regulation (EC) No 396/2005 imposes on Member States the obligation to carry out controls to ensure that food placed on the market is compliant with the legal limits.

A sample is considered <strong>free of quantifiable residues</strong> if the analytes were not present in concentrations at or above the limit of quantification (LOQ). The LOQ is the smallest concentration of an analyte that can be quantified with the analytical method used to analyse the sample. It is commonly defined as the minimum concentration of the analyte in the test sample that can be determined with acceptable precision and accuracy.

If a sample is <strong>contains quantifiable residues</strong> but within the legally permitted limit (maximum residue level, MRL), it is described as a sample  with quantified residue levels within the legal limits (below or at the MRL)

A sample is considered <strong>non-compliant</strong> with the legal limit (MRL), if the measured residue concentrations clearly exceed the legal limits, taking into account the measurement uncertainty. It is current practice that the uncertainty of the analytical measurement is taken into account before legal or administrative sanctions are imposed on food business operators for infringement of the MRL legislation.
description: data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.2587869
title: Latvian results from the monitoring of pesticide residues in food

description: This dataset contains the analytical results of pesticide residues measured in the food products analysed by the national competent authorities. Pesticide residues resulting from the use of plant protection products on crops that are used for food or feed production may pose a risk factor for public health. For this reason, a comprehensive legislative framework has been established in the European Union (EU), which defines rules for the approval of active substances used in plant protection products, the use of plant protection products and for pesticide residues in food. In order to ensure a high level of consumer protection, legal limits, so called “maximum residue levels” or briefly “MRLs”, are established in Regulation (EC) No 396/2005. EU-harmonised MRLs are set for all pesticides covering all types of food products. A default MRL of 0.01 mg/kg is applicable for pesticides not explicitly mentioned in the MRL legislation. Regulation (EC) No 396/2005 imposes on Member States the obligation to carry out controls to ensure that food placed on the market is compliant with the legal limits. A sample is considered <strong>free of quantifiable residues</strong> if the analytes were not present in concentrations at or above the limit of quantification (LOQ). The LOQ is the smallest concentration of an analyte that can be quantified with the analytical method used to analyse the sample. It is commonly defined as the minimum concentration of the analyte in the test sample that can be determined with acceptable precision and accuracy. If a sample is <strong>contains quantifiable residues</strong> but within the legally permitted limit (maximum residue level, MRL), it is described as a sample with quantified residue levels within the legal limits (below or at the MRL) A sample is considered <strong>non-compliant</strong> with the legal limit (MRL), if the measured residue concentrations clearly exceed the legal limits, taking into account the measurement uncertainty. It is current practice that the uncertainty of the analytical measurement is taken into account before legal or administrative sanctions are imposed on food business operators for infringement of the MRL legislation.
description: data.collection@efsa.europa.eu We are seeking feedback on our open data please complete the survey at the link below https://ec.europa.eu/eusurvey/runner/9344dfa0-f384-cb72-65f6-6c187a6d0f14
DOI: 10.25810/jck1-hf50.85
title: US Newspaper Coverage of Climate Change or Global Warming, 2000-2025 - April 2025

description: The Media and Climate Change Observatory Data monitors 127 sources (across newspapers, radio and TV) in 59 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.15468/dl.jjcyw5
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Delphinium biternatum Huth",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation)"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030712-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qjtuph
title: Occurrence Download

description: A dataset containing 229 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "GadmGid is one of (ECU.8.3_1, ECU.8.1_1, ECU.8.4_1, ECU.8.5_1, ECU.14.16_1, ECU.14.10_1, ECU.14.21_1, ECU.14.3_1, ECU.14.8_1, ECU.14.11_1, ECU.14.14_1, ECU.21.2_1, ECU.21.1_1, ECU.13.2_1, ECU.13.8_1, ECU.13.12_1, ECU.13.13_1, ECU.10.11_1, ECU.10.7_1, ECU.10.21_1, ECU.10.6_1, ECU.10.14_1, ECU.10.22_1, ECU.10.16_1, ECU.20.3_1, ECU.20.2_1, ECU.20.1_1, ECU.7.8_1, ECU.7.13_1, ECU.7.10_1, ECU.7.6_1, ECU.7.1_1, ECU.4.6_1, ECU.4.3_1, ECU.4.4_1, ECU.11.3_1, ECU.11.4_1, ECU.11.2_1, ECU.11.1_1, ECU.19.6_1, ECU.19.1_1, ECU.19.7_1, ECU.19.8_1, ECU.6.2_1, ECU.6.5_1, ECU.6.4_1, ECU.6.6_1, ECU.23.1_1, ECU.23.2_1, ECU.23.7_1, ECU.23.8_1, ECU.2.5_1, ECU.2.7_1, ECU.2.2_1, ECU.5.10_1, ECU.5.1_1, ECU.5.6_1, ECU.5.4_1, ECU.3.1_1, ECU.3.2_1, ECU.3.3_1, ECU.3.5_1, ECU.1.3_1, ECU.1.7_1, ECU.1.10_1, ECU.1.2_1, ECU.12.7_1, ECU.12.2_1, ECU.7.14_1, ECU.22.4_1, ECU.22.6_1, ECU.16.5_1, ECU.16.1_1, ECU.16.3_1, ECU.17.4_1, ECU.17.2_1, ECU.18.4_1, ECU.18.2_1, ECU.18.5_1, ECU.15.1_1, ECU.15.3_1, ECU.15.5_1, ECU.24.9_1, ECU.24.8_1, ECU.24.2_1, ECU.9.2_1, ECU.9.3_1, ECU.9.1_1)",
 "IucnRedListCategory is one of (EX, EW, CR, EN, VU, NT, LC, DD, NE)",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Chromista, Bacteria)",
 "Year 1991-2021"
 ]
}

 The dataset includes 229 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030714-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15411195
title: Three-photon Rabi oscillations in N$_2^+$ lasing at 391 nm

description: This dataset contains all numerical data corresponding to the figures presented in the study “Three-photon Rabi oscillations in N$_2^+$ lasing at 391 nm”. It includes the time-dependent population inversion at 391 nm under various pump laser wavelengths and laser intensities.

All simulations were performed using a Fortran-based computational package developed by the authors. The dataset supports Figures 1–4 and Figures A1–A2 of the associated manuscript and is provided to ensure reproducibility and to facilitate further analysis by other researchers in the field of laser–molecule interactions.

If you use this dataset, please cite it accordingly.
DOI: 10.5281/zenodo.15411196
title: Three-photon Rabi oscillations in N$_2^+$ lasing at 391 nm

description: This dataset contains all numerical data corresponding to the figures presented in the study “Three-photon Rabi oscillations in N$_2^+$ lasing at 391 nm”. It includes the time-dependent population inversion at 391 nm under various pump laser wavelengths and laser intensities.

All simulations were performed using a Fortran-based computational package developed by the authors. The dataset supports Figures 1–4 and Figures A1–A2 of the associated manuscript and is provided to ensure reproducibility and to facilitate further analysis by other researchers in the field of laser–molecule interactions.

If you use this dataset, please cite it accordingly.
DOI: 10.15468/dl.wwnvh7
title: Occurrence Download

description: A dataset listing the 21 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-73.31179 44.69324,-73.72234 40.49536,-69.45261 40.71603,-68.78033 43.34355,-68.4211 45.32446,-73.31179 44.69324))",
 "HasCoordinate is true",
 "TaxonKey is Cuscuta L."
 ]
}

 The dataset's 21 records were derived from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030725-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25810/c862-0e81.85
title: US Television Coverage of Climate Change or Global Warming, 2000-2025 - April 2025

description: The Media and Climate Change Observatory Data monitors 130 sources (across newspapers, radio and TV) in 59 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.15468/dl.r34pvg
title: Occurrence Download

description: A dataset listing the 2070 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Swiss National Lichens Databank"
 ]
}

 The dataset's 2070 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030729-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11067593
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Greece

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 – Hellenic Food Authority, Ministry of Rural Development and Food

OCC-CHEMMON2021 – Hellenic Food Authority, Ministry of Rural Development and Food

OCC-CHEMMON2022 – Hellenic Food Authority, Ministry of Rural Development and Food

OCC-CHEMMON2023 – Hellenic Food Authority, Ministry of Rural Development and Food
description: GR; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.15411644
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Greece

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 – Hellenic Food Authority, Ministry of Rural Development and Food

OCC-CHEMMON2021 – Hellenic Food Authority, Ministry of Rural Development and Food

OCC-CHEMMON2022 – Hellenic Food Authority, Ministry of Rural Development and Food

OCC-CHEMMON2023 – Hellenic Food Authority, Ministry of Rural Development and Food

OCC-CHEMMON2024 – Hellenic Food Authority, Ministry of Rural Development and Food
description: GR; CSV; data.collection@efsa.europa.eu