cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7034497
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Portugal

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 – National Institute of Health Doutor Ricardo Jorge

OCC-CHEMMON2021 – National Institute of Health Doutor Ricardo Jorge

OCC-CHEMMON2022 – National Institute of Health Doutor Ricardo Jorge

OCC-CHEMMON2023 – National Institute of Health Doutor Ricardo Jorge

OCC-CHEMMON2024 – National Institute of Health Doutor Ricardo Jorge
description: PT; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.7034498
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Portugal

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 – National Institute of Health Doutor Ricardo Jorge
description: PT; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.7038143
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Portugal

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 – National Institute of Health Doutor Ricardo Jorge OCC-CHEMMON2021 – National Institute of Health Doutor Ricardo Jorge
description: PT; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.7808600
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Portugal

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 – National Institute of Health Doutor Ricardo Jorge OCC-CHEMMON2021 – National Institute of Health Doutor Ricardo Jorge OCC-CHEMMON2022 – National Institute of Health Doutor Ricardo Jorge
description: PT; CSV; data.collection@efsa.europa.eu
DOI: 10.7910/dvn/19yx85
title: EFL students’ Perspectives on Integrating Sustainable Development Goals (SDGs)-Climate Change content in English Language Classrooms in North Macedonia

description: This dataset includes SPSS output showing descriptive statistical results from a survey conducted with university students in North Macedonia. The survey aimed to explore their perceptions of the relevance, visibility, and educational value of integrating Sustainable Development Goals (SDGs) into English as a Foreign Language (EFL) instruction. The findings provide insights into student awareness and support for sustainability in language education.
description: Data collection period: October-November 2024
Anonymity and ethical guidelines were upheld throughout the data collection process.
These findings are derived from the ongoing Doctoral Thesis titled“The Integration of Sustainable Development Goals—Climate Change in English as a Foreign Language Classroom and Curricula at the Universities of North Macedonia”
Author, PhD Candidate: Zylfije Tahiri
DOI: 10.15468/dl.qayx7a
title: Occurrence Download

description: A dataset containing 7432 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Apodemus sylvaticus (Linnaeus, 1758)",
 "Geometry POLYGON((-8.00174339329464 54.1998526673513, 0.202120938926891 54.1998526673513, 0.202120938926891 61.2628565887411, -8.00174339329464 61.2628565887411, -8.00174339329464 54.1998526673513))",
 "CoordinateUncertaintyInMeters is 0,101",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7432 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013619-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fwed6h
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2025",
 "TaxonKey is Actinopterygii"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013620-250426092105405/datasets/export for details.
DOI: 10.5281/zenodo.15211740
title: CppSATD: A Reusable Self-Admitted Technical Debt Dataset in C++

description: CppSATD is the first dedicated C++ SATD comments dataset comprising multi-class SATD comments along with their code context. It is the largest available multi-type SATD dataset with surrounding code context, comprising over 13k manually annotated SATD comments grouped under different types of SATD.



silver_standard_cpp.csv: The silver standard dataset comprises a total of 531,367 source code comments from all five repositories identified. We perform an automated annotation for SATD on the entire dataset using the established SATD text patterns from the PENTACET corpus. The automated annotation resulted in 18,973 SATD comments. The remaining 512,394 are treated as NON-SATD comments. This dataset does not involve any human verification but is solely based on the SATD patterns from the PENTACET corpus.

gold_standard_cpp.csv: We utilize the SATD comments from the silver standard data. We manually verified the 18,973 comments to validate if they are SATD. To ascertain that the 512,394 are NON-SATD comments at 99% confidence level and 1% margin of error, we take a random sample of 16,125 source code comments from 512,394 comments. Overall, the manual verification resulted in a total of 13,069 SATD comments and 22,029 NON-SATD comments. The 13,069 is further classified into one of the five types of SATD as identified in the seminar work that introduced the concept of SATD.

repos.zip: This includes the source code of 5 C++ repositories, from which we collected the data.
DOI: 10.5281/zenodo.15209561
title: CppSATD: A Reusable Self-Admitted Technical Debt Dataset in C++

description: CppSATD is the first dedicated C++ SATD comments dataset comprising multi-class SATD comments along with their code context. It is the largest available multi-type SATD dataset with surrounding code context, comprising over 13k manually annotated SATD comments grouped under different types of SATD.



silver_standard_cpp.csv: The silver standard dataset comprises a total of 531,367 source code comments from all five repositories identified. We perform an automated annotation for SATD on the entire dataset using the established SATD text patterns from the PENTACET corpus. The automated annotation resulted in 18,973 SATD comments. The remaining 512,394 are treated as NON-SATD comments. This dataset does not involve any human verification but is solely based on the SATD patterns from the PENTACET corpus.

gold_standard_cpp.csv: We utilize the SATD comments from the silver standard data. We manually verified the 18,973 comments to validate if they are SATD. To ascertain that the 512,394 are NON-SATD comments at 99% confidence level and 1% margin of error, we take a random sample of 16,125 source code comments from 512,394 comments. Overall, the manual verification resulted in a total of 13,069 SATD comments and 22,029 NON-SATD comments. The 13,069 is further classified into one of the five types of SATD as identified in the seminar work that introduced the concept of SATD.

repos.zip: This includes the source code of 5 C++ repositories, from which we collected the data.

Official_workshop_document.pdf: This document was created to ensure a consistent understanding regarding SATD types between the authors.
DOI: 10.5281/zenodo.15209562
title: CppSATD: A Reusable Self-Admitted Technical Debt Dataset in C++

description: CppSATD is the first dedicated C++ SATD comments dataset comprising multi-class SATD comments along with their code context. It is the largest available multi-type SATD dataset with surrounding code context, comprising over 13k manually annotated SATD comments grouped under different types of SATD.



silver_standard_cpp.csv: The silver standard dataset comprises a total of 531,367 source code comments from all five repositories identified. We perform an automated annotation for SATD on the entire dataset using the established SATD text patterns from the PENTACET corpus. The automated annotation resulted in 18,973 SATD comments. The remaining 512,394 are treated as NON-SATD comments. This dataset does not involve any human verification but is solely based on the SATD patterns from the PENTACET corpus.

gold_standard_cpp.csv: We utilize the SATD comments from the silver standard data. We manually verified the 18,973 comments to validate if they are SATD. To ascertain that the 512,394 are NON-SATD comments at 99% confidence level and 1% margin of error, we take a random sample of 16,125 source code comments from 512,394 comments. Overall, the manual verification resulted in a total of 13,069 SATD comments and 22,029 NON-SATD comments. The 13,069 is further classified into one of the five types of SATD as identified in the seminar work that introduced the concept of SATD.

repos.zip: This includes the source code of 5 C++ repositories, from which we collected the data.
DOI: 10.5281/zenodo.15224656
title: CppSATD: A Reusable Self-Admitted Technical Debt Dataset in C++

description: CppSATD is the first dedicated C++ SATD comments dataset comprising multi-class SATD comments along with their code context. It is the largest available multi-type SATD dataset with surrounding code context, comprising over 13k manually annotated SATD comments grouped under different types of SATD.



silver_standard_cpp.csv: The silver standard dataset comprises a total of 531,367 source code comments from all five repositories identified. We perform an automated annotation for SATD on the entire dataset using the established SATD text patterns from the PENTACET corpus. The automated annotation resulted in 18,973 SATD comments. The remaining 512,394 are treated as NON-SATD comments. This dataset does not involve any human verification but is solely based on the SATD patterns from the PENTACET corpus.

gold_standard_cpp.csv: We utilize the SATD comments from the silver standard data. We manually verified the 18,973 comments to validate if they are SATD. To ascertain that the 512,394 are NON-SATD comments at 99% confidence level and 1% margin of error, we take a random sample of 16,125 source code comments from 512,394 comments. Overall, the manual verification resulted in a total of 13,069 SATD comments and 22,029 NON-SATD comments. The 13,069 is further classified into one of the five types of SATD as identified in the seminar work that introduced the concept of SATD.

repos.zip: This includes the source code of 5 C++ repositories, from which we collected the data.

Official_workshop_document.pdf: This document was created to ensure a consistent understanding regarding SATD types between the authors.
DOI: 10.15468/dl.x6xhhn
title: Occurrence Download

description: A dataset containing 7300 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Limacus maculatus (Kaleniczenko, 1851)"
 ]
}

 The dataset includes 7300 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011282-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sast62
title: Occurrence Download

description: A dataset containing 580 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mylia verrucosa Lindb."
 ]
}

 The dataset includes 580 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0075631-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ws5pqe
title: Occurrence Download

description: A dataset containing 794237131 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 794237131 records from 11132 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0326191-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r2a6hq
title: Occurrence Download

description: A dataset containing 2498 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Agonis (DC.) Sweet"
 ]
}

 The dataset includes 2498 records from 108 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097204-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u2j28s
title: Occurrence Download

description: A dataset containing 610 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Actinodium Schauer ex Schltdl."
 ]
}

 The dataset includes 610 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088206-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9yfmtq
title: Occurrence Download

description: A dataset containing 53973 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Angophora Cav."
 ]
}

 The dataset includes 53973 records from 127 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088285-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mu9v37
title: Occurrence Download

description: A dataset containing 476 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Allosyncarpia S.T.Blake"
 ]
}

 The dataset includes 476 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088249-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4rx9n6
title: Occurrence Download

description: A dataset containing 228 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arillastrum Pancher ex Brongn. & Gris"
 ]
}

 The dataset includes 228 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088373-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yr7m73
title: Occurrence Download

description: A dataset containing 2502 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astartea DC."
 ]
}

 The dataset includes 2502 records from 80 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088378-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b7bj6a
title: Occurrence Download

description: A dataset containing 223 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astus Trudgen & Rye"
 ]
}

 The dataset includes 223 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097235-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gu4xvw
title: Occurrence Download

description: A dataset containing 2738 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Asteromyrtus Schauer"
 ]
}

 The dataset includes 2738 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088387-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.32w4uf
title: Occurrence Download

description: A dataset containing 8321 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Backhousia Hook. & Harv."
 ]
}

 The dataset includes 8321 records from 95 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088394-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9qxnyf
title: Occurrence Download

description: A dataset containing 19927 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Baeckea L."
 ]
}

 The dataset includes 19927 records from 141 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088398-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f6yjjj
title: Occurrence Download

description: A dataset containing 375 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Balaustion Hook."
 ]
}

 The dataset includes 375 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088403-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z5u6qv
title: Occurrence Download

description: A dataset containing 166 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Barongia Peter G.Wilson & B.Hyland"
 ]
}

 The dataset includes 166 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088408-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e3mzma
title: Occurrence Download

description: A dataset containing 40883 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Callistemon R.Br."
 ]
}

 The dataset includes 40883 records from 513 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088865-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.