cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.3phujj
title: Occurrence Download

description: A dataset containing 165 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Callosciurus erythraeus",
 "Country is Japan",
 "HasCoordinate is true"
 ]
}

 The dataset includes 165 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032519-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3e5fbp
title: Occurrence Download

description: A dataset containing 1171 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is The New York Botanical Garden Herbarium (NY)",
 "Country is Croatia"
 ]
}

 The dataset includes 1171 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032515-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5x99nk
title: Occurrence Download

description: A dataset containing 4830606 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pterygoplichthys pardalis, Lagarosiphon major, Toona ciliata, Silurus glanis, Asparagus setaceus, Cosmos caudatus, Calotropis gigantea, Bassia scoparia, Cervus elaphus, Limnoperna fortunei, Physella acuta, Eragrostis curvula, Digitaria sanguinalis, Lolium multiflorum, Cichorium intybus, Artemisia annua, Senecio madagascariensis, Cerastium glomeratum, Fallopia convolvulus, Rumex obtusifolius, Trifolium pratense, Vinca major, Plantago major, Grevillea robusta, Elaeagnus angustifolia, Pyracantha coccinea, Citrus aurantium, Pinus halepensis, Pinus pinaster, Eclipta prostrata, Genista monspessulana, Prosopis glandulosa, Amphibalanus improvisus, Callinectes sapidus, Annona glabra, Xiphophorus hellerii, Heliotropium indicum, Limnocharis flava, Terminalia catappa, Cryptotermes brevis, Ziziphus mauritiana, Heracleum sosnowskyi, Erigeron strigosus, Sambucus racemosa, Striga hermonthica, Sorbaria sorbifolia, Hyparrhenia rufa, Lepidium virginicum, Panicum capillare, Alternanthera pungens)",
 "BasisOfRecord is one of (Machine Observation, Human Observation, Observation)",
 "HasCoordinate is true",
 "Year is greater than or equal to 1990"
 ]
}

 The dataset includes 4830606 records from 6096 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032488-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zmywsp
title: Occurrence Download

description: A dataset containing 112 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tragopan caboti (Gould, 1857), Muntiacus crinifrons (Sclater, 1885), Ursus thibetanus G)",
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation, Occurrence evidence, Literature Occurrence)",
 "Country is China",
 "Geometry POLYGON((114.459123 23.073075,120.760536 23.073075,120.760536 29.251706,114.459123 29.251706,114.459123 23.073075))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2019",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 112 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003059-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/11846682
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.15468/dl.8czcf5
title: Occurrence Download

description: A dataset containing 6023 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((22.18712 42.99350,66.66232 42.99350,66.66232 60.76338,22.18712 60.76338,22.18712 42.99350))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Arrhenatherum elatius (L.) P.Beauv. ex J.Presl & C.Presl"
 ]
}

 The dataset includes 6023 records from 108 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003060-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v73jd4
title: Occurrence Download

description: A dataset containing 138271 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "DatasetKey is EOD – eBird Observation Dataset",
 "GadmGid is CHN.24_1"
 ]
}

 The dataset includes 138271 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003050-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15449470
title: tadorna_tadorna_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.15449471
title: tadorna_tadorna_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.15449458
title: INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES INTO HIGHER EDUCATION IN UZBEKISTAN: ASPECTS, CHALLENGES AND DEVELOPMENT PATHWAYS

description: The article analyses the pre-conditions, current state and projected trajectories of integrating artificial intelligence (AI) into Uzbekistan’s higher-education system. Drawing upon a systematic review of 312 peer-reviewed articles, a two-round Delphi study with 22 national experts, institutional surveys covering 15 universities (n = 420) and multiple case studies, the paper identifies four dominant research clusters—adaptive learning, learning-analytics, generative academic support and AI ethics—and benchmarks domestic progress against leading international implementations. Empirical findings show that student AI adoption in Uzbekistan rose from 31 % in 2024 to 57 % in 2025, yet only 10 % of public institutions report fully integrated AI strategies. Key barriers include insufficient broadband capacity (< 100 Mbit s⁻¹ in 40 % of campuses), shortage of AI-literate faculty (0.8 specialists per 1 000 students) and limited regulatory guidance. Comparative evidence from Arizona State University and SeoulTech confirms measurable gains in grade-point averages (+0.2) and a 19 % reduction in course-completion times. The study proposes a phased roadmap (2025-2030) focused on infrastructure upgrading, compulsory AI-literacy modules, two-tier ethical governance and industry–academic laboratories. Implementing these measures could raise the share of AI-enabled courses to 35 % and improve Uzbekistan’s position in the Government AI Readiness Index by at least ten ranks.
DOI: 10.5281/zenodo.15449459
title: INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES INTO HIGHER EDUCATION IN UZBEKISTAN: ASPECTS, CHALLENGES AND DEVELOPMENT PATHWAYS

description: The article analyses the pre-conditions, current state and projected trajectories of integrating artificial intelligence (AI) into Uzbekistan’s higher-education system. Drawing upon a systematic review of 312 peer-reviewed articles, a two-round Delphi study with 22 national experts, institutional surveys covering 15 universities (n = 420) and multiple case studies, the paper identifies four dominant research clusters—adaptive learning, learning-analytics, generative academic support and AI ethics—and benchmarks domestic progress against leading international implementations. Empirical findings show that student AI adoption in Uzbekistan rose from 31 % in 2024 to 57 % in 2025, yet only 10 % of public institutions report fully integrated AI strategies. Key barriers include insufficient broadband capacity (< 100 Mbit s⁻¹ in 40 % of campuses), shortage of AI-literate faculty (0.8 specialists per 1 000 students) and limited regulatory guidance. Comparative evidence from Arizona State University and SeoulTech confirms measurable gains in grade-point averages (+0.2) and a 19 % reduction in course-completion times. The study proposes a phased roadmap (2025-2030) focused on infrastructure upgrading, compulsory AI-literacy modules, two-tier ethical governance and industry–academic laboratories. Implementing these measures could raise the share of AI-enabled courses to 35 % and improve Uzbekistan’s position in the Government AI Readiness Index by at least ten ranks.
DOI: 10.15468/dl.zn954c
title: Occurrence Download

description: A dataset containing 616742 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Actitis hypoleucos (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than 1989",
 "Year is less than 2026",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is Absent"
 ]
 }
 },
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 616742 records from 589 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003055-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p2a3ud
title: Occurrence Download

description: A dataset containing 1962 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((21.13170 47.27617,66.88676 47.27617,66.88676 65.55742,21.13170 65.55742,21.13170 47.27617))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Sorbaronia ×arsenii (Britton & Arsène) G.N.Jones"
 ]
}

 The dataset includes 1962 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003061-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uqf7mf
title: Occurrence Download

description: A dataset containing 71726 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Hippuris L."
 ]
}

 The dataset includes 71726 records from 661 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003057-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g96wxr
title: Occurrence Download

description: A dataset containing 70 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Africa",
 "TaxonKey is Eucalyptus grandis W.Hill ex Maiden"
 ]
}

 The dataset includes 70 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003063-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.687rx8
title: Occurrence Download

description: A dataset containing 10659 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is Morchella esculenta (L.) Pers.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 10659 records from 249 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003062-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ugkqty
title: Occurrence Download

description: A dataset containing 26246 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Deutzia Thunb."
 ]
}

 The dataset includes 26246 records from 361 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030590-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qpj6df
title: Occurrence Download

description: A dataset listing the 1 species recorded 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 Oomycota",
 "Year 1991-2021"
 ]
}

 The dataset's 1 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030584-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14920705
title: AFCD: An Annual Cropland Extent Dataset for Africa at 30m Spatial Resolution from 2000 to 2022

description: Accurate cropland mapping is essential for understanding agricultural dynamics in Africa, a critical global issue with significant implications for the Sustainable Development Goals (e.g., Zero Hunger). The AFCD (Africa Cropland Dataset) 2000-2022 is a 30-meter resolution annual cropland mapping product covering the African continent. Comprising 23 independent GeoTIFF files named "AFCD_YYYY.tif" (where YYYY ranges from 2000 to 2022), each file utilizes a binary classification scheme: pixel value 1 indicates cropland areas and 0 represents non-cropland. Accurate cropland mapping is essential for understanding agricultural dynamics in Africa, a critical global issue with significant implications for the Sustainable Development Goals (e.g., Zero Hunger).
DOI: 10.5281/zenodo.14920706
title: AFCD: An Annual Cropland Extent Dataset for Africa at 30m Spatial Resolution from 2000 to 2022

description: Accurate cropland mapping is essential for understanding agricultural dynamics in Africa, a critical global issue with significant implications for the Sustainable Development Goals (e.g., Zero Hunger). The AFCD (Africa Cropland Dataset) 2000-2022 is a 30-meter resolution annual cropland mapping product covering the African continent. Comprising 23 independent GeoTIFF files named "AFCD_YYYY.tif" (where YYYY ranges from 2000 to 2022), each file utilizes a binary classification scheme: pixel value 1 indicates cropland areas and 0 represents non-cropland. Accurate cropland mapping is essential for understanding agricultural dynamics in Africa, a critical global issue with significant implications for the Sustainable Development Goals (e.g., Zero Hunger).
DOI: 10.5281/zenodo.11073611
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Norway

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, and 2023, 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-CHEMMON2023 – Institute of Marine Research

OCC-CHEMMON2023 – Norwegian Institute of Bioeconomy Research

OCC-CHEMMON2024 – Institute of Marine Research

OCC-CHEMMON2024 – Norwegian Institute of Bioeconomy Research
description: NO; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.11073612
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Norway

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 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-CHEMMON2023 – Institute of Marine Research

OCC-CHEMMON2023 – Norwegian Institute of Bioeconomy Research
description: NO; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.15411135
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Norway

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, and 2023, 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-CHEMMON2023 – Institute of Marine Research

OCC-CHEMMON2023 – Norwegian Institute of Bioeconomy Research

OCC-CHEMMON2024 – Institute of Marine Research

OCC-CHEMMON2024 – Norwegian Institute of Bioeconomy Research
description: NO; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.15305314
title: Identification of a large anion channel required for digestive vacuole acidification and amino acid export in Plasmodium falciparum
DOI: 10.5281/zenodo.15305315
title: Identification of a large anion channel required for digestive vacuole acidification and amino acid export in Plasmodium falciparum
DOI: 10.5281/zenodo.15313529
title: Identification of a large anion channel required for digestive vacuole acidification and amino acid export in Plasmodium falciparum
DOI: 10.5281/zenodo.15411270
title: Identification of a large anion channel required for digestive vacuole acidification and amino acid export in Plasmodium falciparum
DOI: 10.15468/dl.j65vwe
title: Occurrence Download

description: A dataset containing 4065 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Culicoides imicola Kieffer, 1913"
 ]
}

 The dataset includes 4065 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030592-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.az345t
title: Occurrence Download

description: A dataset containing 148 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acanthosaura phuketensis Pauwels, Sumontha, Kunya, Nitikul, Samphanthamit, Wood & Grismer, 2015"
 ]
}

 The dataset includes 148 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030594-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.2908/met_ipr_da
title: Community design (CD) applications by metropolitan region (1996-2016)
title: Anmeldungen von Gemeinschaftsgeschmacksmustern (CD) nach Metropolregionen (1996-2016)
title: Demandes de dessins ou modèles communautaires (CD) par région métropolitaine (1996-2016)
DOI: 10.2908/met_ipr_dagdp
title: Demandes de dessins ou modèles communautaires (CD) par milliards de PIB et région métropolitaine (1996-2016)
title: Anmeldungen von Gemeinschaftsgeschmacksmustern (CD) pro Milliarden BIP nach Metropolregionen (1996-2016)
title: Community design (CD) applications per billion GDP by metropolitan region (1996-2016)
DOI: 10.2908/met_ipr_dapop
title: Community design (CD) applications per million population by metropolitan region (1996-2016)
title: Demandes de dessins ou modèles communautaires (CD) par millions d'habitants et région métropolitaine (1996-2016)
title: Anmeldungen von Gemeinschaftsgeschmacksmustern (CD) pro Millionen Einwohner nach Metropolregionen (1996-2016)
DOI: 10.2908/met_ipr_dfa
title: Gemeinschaftsgeschmacksmuster (CD) nach Metropolregionen (1996-2016)
title: Dessins ou modèles communautaires (CD) par région métropolitaine (1996-2016)
title: Community designs (CD) by metropolitan region (1996-2016)