cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26050/wdcc/ar6.ipcc-ar6_reg_spo_tasmin
title: IPCC-AR6_CMIP6 Regional Subset South Pole tasmin

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6).

CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ).

The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide.
Summary: These data include a subset of the CMIP6 input data assessed by the IPCC AR6 WGI authors for region South Pole (180°W - 180°E, 90°S - 57°S). Included is the monthly mean minimum air temperature in 2m height (tasmin) data of the experiments historical, ssp126, ssp245, ssp370, and ssp585 for models providing more than 5 out of 12 core variables. 

Further details are provided in the additional information "IPCC AR6 Data for Regions".
DOI: 10.26050/wdcc/ar6.ipcc-ar6_reg_spo_uas
title: IPCC-AR6_CMIP6 Regional Subset South Pole uas

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6).

CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ).

The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide.
Summary: These data include a subset of the CMIP6 input data assessed by the IPCC AR6 WGI authors for region South Pole (180°W - 180°E, 90°S - 57°S). Included is the monthly mean eastward wind in 10m height (uas) data of the experiments historical, ssp126, ssp245, ssp370, and ssp585 for models providing more than 5 out of 12 core variables. 

Further details are provided in the additional information "IPCC AR6 Data for Regions".
DOI: 10.26050/wdcc/ar6.ipcc-ar6_reg_spo_vas
title: IPCC-AR6_CMIP6 Regional Subset South Pole vas

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6).

CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ).

The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide.
Summary: These data include a subset of the CMIP6 input data assessed by the IPCC AR6 WGI authors for region South Pole (180°W - 180°E, 90°S - 57°S). Included is the monthly mean westward wind in 10m height (vas) data of the experiments historical, ssp126, ssp245, ssp370, and ssp585 for models providing more than 5 out of 12 core variables. 

Further details are provided in the additional information "IPCC AR6 Data for Regions".
DOI: 10.34740/kaggle/dsv/10928330
title: Hacker News Cumulative Data
DOI: 10.5281/zenodo.14971513
title: Dataset for the paper "Local defect simulation by means of the distributed circuit modelling"

description: Dataset for the paper "Local defect simulation by means of the distributed circuit modelling" published at AIP Conf. Proc. 2487, 040003 (2022)https://doi.org/10.1063/5.0089323
DOI: 10.5281/zenodo.14971512
title: Dataset for the paper "Local defect simulation by means of the distributed circuit modelling"

description: Dataset for the paper "Local defect simulation by means of the distributed circuit modelling" published at AIP Conf. Proc. 2487, 040003 (2022)https://doi.org/10.1063/5.0089323
DOI: 10.48320/89d1f3e7-6e73-4975-aefc-f10b26808a1b
title: Trust in Social and Political Institutions: Public Opinion in Ukraine (2012-2024)
DOI: 10.34740/kaggle/dsv/10928264
title: The Healthcare Dataset
DOI: 10.15468/dl.pwug4t
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Bulbophyllum bicoloratum Schltr."
 ]
}

 The dataset includes 25 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005890-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14971686
title: Rebuilding Trust: E-commerce Efforts to Overcome Fraud Impacts and Enhance Consumer Loyalty

description: E-commerce has transformed the global marketplace, offering convenience but also increasing fraud risks such as payment fraud, account takeovers, and fake reviews, which erode consumer trust and affect brand loyalty. This study examines the impact of fraud on consumer confidence and evaluates mitigation strategies used by e-commerce platforms.Based on a survey of 450 respondents from Jakarta (55%), Surabaya (20%), Bandung (15%), and Medan (10%), the sample includes 52% male and 48% female, aged 18-45 years. Participants were selected for their active engagement in online shopping.Key fraud prevention measures analyzed include AI-powered detection systems, blockchain for secure transactions, and biometric authentication. Trust-building strategies such as transparent return policies, improved customer service, and security notifications are also assessed. Additionally, the study explores the role of regulations and industry collaboration in combating fraud.Through case studies and empirical research, this paper emphasizes a multi-layered security approach and customer-centric recovery strategies to restore trust and ensure long-term consumer loyalty. The findings offer practical insights for businesses enhancing fraud prevention while maintaining a positive user experience.
DOI: 10.5281/zenodo.14971687
title: Rebuilding Trust: E-commerce Efforts to Overcome Fraud Impacts and Enhance Consumer Loyalty

description: E-commerce has transformed the global marketplace, offering convenience but also increasing fraud risks such as payment fraud, account takeovers, and fake reviews, which erode consumer trust and affect brand loyalty. This study examines the impact of fraud on consumer confidence and evaluates mitigation strategies used by e-commerce platforms.Based on a survey of 450 respondents from Jakarta (55%), Surabaya (20%), Bandung (15%), and Medan (10%), the sample includes 52% male and 48% female, aged 18-45 years. Participants were selected for their active engagement in online shopping.Key fraud prevention measures analyzed include AI-powered detection systems, blockchain for secure transactions, and biometric authentication. Trust-building strategies such as transparent return policies, improved customer service, and security notifications are also assessed. Additionally, the study explores the role of regulations and industry collaboration in combating fraud.Through case studies and empirical research, this paper emphasizes a multi-layered security approach and customer-centric recovery strategies to restore trust and ensure long-term consumer loyalty. The findings offer practical insights for businesses enhancing fraud prevention while maintaining a positive user experience.
DOI: 10.5281/zenodo.14629433
title: SVModeller Data

description: Sample data to run SVModeller, a computational tool to simulate synthetic human haplotypes containing embedded structural variants.
DOI: 10.15468/dl.5avfrm
title: Occurrence Download

description: A dataset containing 224 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is one of (Estonia, Finland, Sweden, Poland, Russian Federation, Åland Islands)",
 "TaxonKey is Cercopagis pengoi (Ostroumov, 1891)"
 ]
}

 The dataset includes 224 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005895-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14967709
title: SVModeller Data v.0.2

description: Sample data to run SVModeller, a computational tool to simulate synthetic human haplotypes containing embedded structural variants.
DOI: 10.15468/dl.c5e9hn
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Convolvulus humilis Jacq.",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 26 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005891-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14730484
title: supporting data
DOI: 10.5281/zenodo.14730485
title: supporting data
DOI: 10.15468/dl.khtg8y
title: Occurrence Download

description: A dataset containing 321 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eryngium galioides Lam.)",
 "BasisOfRecord is one of (Human Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 321 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005896-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17631/rd-2025-0004-ddat
title: Exploring CERT Mentor activities in the School of Social Sciences

description: SPUR funded project to explore the activities of CERT Mentors within School of Social Sciences. CERT Mentors are a key aspect of induction and supporting transitions, but currently there’s little evaluation and sharing of best practice. This project, through focus groups with CERT Mentor course leads, will develop an understanding of how Mentors are used, what works well and any challenges experienced. This will form a benchmarking exercise of CERT Mentor activity and contribute to developments of the role.
DOI: 10.15468/dl.8d5a33
title: Occurrence Download

description: A dataset containing 383 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Termitomyces microcarpus (Berk. & Broome) R.Heim"
 ]
}

 The dataset includes 383 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005897-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rjkmnh
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Convolvulus meonanthus Hoffmanns. & Link",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 20 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005892-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9d6sxq
title: Occurrence Download

description: A dataset containing 614578 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Argonautidae, Ommastrephidae, Ocythoidae, Mysidae, Cancridae, Grapsidae, Strongylocentrotidae, Echinometridae, Echinometradae, Crangonidae, Goneplacidae, Xanthidae, Euphausiidae, Pasiphaeidae, Oikopleuridae, Paracalanidae, Centropagidae, Corycaeidae, Clausocalanidae, Calanidae, Eucalanidae, Rhincalanidae, Aetideidae, Euchaetidae, Scolecitrichidae, Candaciidae, Temoridae, Oithonidae, Sapphirinidae, Oncaeidae, Caligidae, Ectinosomatidae, Pinnotheridae, Alloposidae, Majidae, Ophiuridae, Hyperiidae, Physaliidae, Porpitidae, Diphyidae, Ulmaridae, Pandeidae, Periphyllidae, Atelecyclidae, Penaeidae, Sepiidae, Vampyroteuthidae, Munididae, Leucosiidae, Sergestidae, Salpidae, Squillidae, Vitreledonellidae, Amphitretidae, Ocypodidae, Pandalidae, Spongicolidae, Lithodidae, Sepiolidae, Onychoteuthidae, Gonatidae, Goniatidae, Alpheidae, Palaemonidae, Stichopodidae, Callionymidae, Gobiidae, Myctophidae, Oplophoridae, Luidiidae, Asteriidae, Asteiidae, Enoploteuthidae, Octopodidae, Sternoptychidae, Tremoctopodidae, Hippolytidae, Paguridae, Parapaguridae, Sagittidae, Loliginidae, Stenothoidae, Melitidae, Dogielinotidae, Ampeliscidae, Atylidae, Dexaminidae, Liljeborgiidae, Oedicerotidae, Tryphosidae, Pleustidae, Pontogeneiidae, Pseudocrangonyctidae, Portunidae, Caprellidae, Ischyroceridae, Mytilidae, Nuculanidae, Propeamussiidae, Yoldiidae, Pectinidae, Semelidae, Anomiidae, Veneridae, Tellinidae, Solenidae, Arcidae, Anatinellidae, Laternulidae, Mactridae, Nuculidae, Nereididae, Oenonidae, Eunicidae, Polynoidae, Lumbrineridae, Alciopidae, Aphroditidae, Sternaspidae, Glyceridae, Pectinariidae, Trichobranchidae, Syllidae, Goniadidae, Magelonidae, Nassariidae, Turritellidae, Cylichnidae, Scaphandridae, Muricidae, Buccinidae, Atlantidae, Turbinidae, Haliotidae, Trochidae, Naticidae, Conidae, Littorinidae, Philinidae, Mitridae, Columbellidae, Potamididae, Nacellidae, Rissoidae, Anatomidae, Margaritidae, Pyramidellidae, Fissurellidae, Acteonidae, Naviculaceae, Rhaphoneidaceae, Catenulaceae, Achnanthaceae, Rhabdonemataceae, Thalassiosiraceae, Thallassiosiraceae, Chaetocerotaceae, Coscinodiscaceae, Melosiraceae, Skeletonemaceae, Skeletonemataceae, Hemiaulaceae, Zosteraceae, Laminariaceae, Sargassaceae, Ulvaceae, Gelidiaceae, Halymeniaceae, Alariaceae, Cavoliniidae, Limacinidae, Clionaidae, Cliidae, Balanidae, Pyrgomatidae, Lepadidae, Scalpellidae, Chthamalidae, Tetraclitidae)",
 "Geometry POLYGON((179 20, 179 50, 120 50, 120 20, 179 20))",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 }
 ]
}

 The dataset includes 614578 records from 550 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005859-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6ajs47
title: Occurrence Download

description: A dataset containing 600 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Juniperus pingii var. wilsonii (Rehd.) Silba"
 ]
}

 The dataset includes 600 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005893-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bjc79t
title: Occurrence Download

description: A dataset containing 123073 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Atriplex patula L.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 123073 records from 887 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005885-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0215886.10fu
title: SH0215886.10FU

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/sh0215887.10fu
title: SH0215887.10FU

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/sh0215888.10fu
title: SH0215888.10FU

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/sh0215889.10fu
title: SH0215889.10FU

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/sh0215890.10fu
title: SH0215890.10FU

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.