cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18771430
title: Dataset Traffic - Induced Air Pollution: PM1, PM2.5, and PM10 Measurements Using Dual enviDUST Sensors at an Urban Intersection

description: This dataset provides high-resolution, 10-minute particulate matter (PM1, PM2.5, and PM10) measurements collected to identify and analyze traffic-induced air pollution. The data were acquired using two enviDUST air quality monitoring sensors mounted on a mobile measurement vehicle located near an intersection. To effectively capture the spatial variance and directional effects of pollutant dispersion, the devices were installed in distinct orientations, as detailed in the attached image. The measurement campaign ran continuously over the summer months of July and August 2025. The final dataset consists of two separate data files, corresponding to the respective enviDUST devices.
DOI: 10.15468/dl.sae3dg
title: Occurrence Download

description: A dataset containing 89999 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is one of (United Kingdom of Great Britain and Northern Ireland, Netherlands, Sweden, Ireland, Belgium, Norway, France)",
 "TaxonKey is Clupea harengus"
 ]
}

 The dataset includes 89999 records from 163 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009934-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18767845
title: Europe Day & Berlin Wall Commemorations on X (Slovenia, Italy, Germany, France): Annotated dataset

description: This Zenodo record contains the research materials for the article “Europe Day and the Fall of the Berlin Wall on Twitter/X: Conflict, Tone, and Deliberative Quality Across France, Germany, Italy, and Slovenia.” It includes the anonymised and annotated datasets used to analyse X posts around Europe Day and the fall of the Berlin Wall in the four countries, the LLM-assisted prompt and the topic-modelling outputs used to identify thematic hotspots of conflict.

We acknowledge support for data access and research infrastructure from the European Union EC/HE/101094752 (SoMe4Dem) and the European Union EC/H2020/101017201 (CIVICA RESEARCH – The European University of Social Sciences – Research and Innovation).
DOI: 10.5281/zenodo.18767846
title: Europe Day & Berlin Wall Commemorations on X (Slovenia, Italy, Germany, France): Annotated dataset

description: This Zenodo record contains the research materials for the article “Europe Day and the Fall of the Berlin Wall on Twitter/X: Conflict, Tone, and Deliberative Quality Across France, Germany, Italy, and Slovenia.” It includes the anonymised and annotated datasets used to analyse X posts around Europe Day and the fall of the Berlin Wall in the four countries, the LLM-assisted prompt and the topic-modelling outputs used to identify thematic hotspots of conflict.

We acknowledge support for data access and research infrastructure from the European Union EC/HE/101094752 (SoMe4Dem) and the European Union EC/H2020/101017201 (CIVICA RESEARCH – The European University of Social Sciences – Research and Innovation).
DOI: 10.25824/redu/ndttjs
title: Dados relativos à coleta de campo da pesquisa: Arranjos e dinâmicas das redes de relacionamento nas unidades de saúde da família em Piracicaba: uma análise de redes sociais

description: Finalidade dos dados: Apoiar a análise das dinâmicas de trabalho em equipe em Unidades de Saúde da Família; Servir de base empírica para avaliar interações interpessoais em equipes multiprofissionais; Fornecer evidências para discutir estratégias de melhoria na atenção primária. Natureza dos dados: Dados quantitativos oriundos de questionário para Análise de Redes Sociais; Base de dados em formato digital (planilhas .xlsx/.csv) Escopo dos dados: Dados coletados entre setembro e dezembro de 2024 em Unidades de Saúde da Família de Piracicaba-SP; Amostra composta por profissionais da estratégia de saúde da família (médicos, enfermeiros, agentes comunitários de saúde, técnicos de enfermagem, dentistas e auxiliares de saúde bucal; Escopo restrito ao estudo de relacionamentos profissionais e não inclui dados clínicos ou de pacientes.
DOI: 10.15468/dl.vybzn2
title: Occurrence Download

description: A dataset containing 84006 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 Hypochaeris radicata",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 84006 records from 367 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009943-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/j26gdxcw7f
title: Type 2 Diabetes Mellitus Real-World Data Preprocessing and Modeling

description: Machine Learning (ML) applied to healthcare Real World Data (RWD) may improve patient management. RWD, however, requires extensive preprocessing to make it ML-ready. The aim of this resource is to explore the impact of preprocessing on ML models applied to RWD from type 2 diabetes patients visits. A GitHub repo is available with the code related to the experiments, to show all the steps we prepared, the decisions we took and alternative pipelines we created.

Work done in partial fulfillment of my PhD dissertation: "Leveraging real-world data with machine learning to disentangle the complexity of multimorbid internal medicine patients"

Linked in the paper: Montagna M, Rabadzhiev AS, Traverso A, Setola E, Draetta E, Dimonte A, Barbieri S, Fabiani B, Piemonti L, Esposito A, Tacchetti C and Rovere Querini P (2026) From raw data to actionable insights: preprocessing real-world data for machine learning in diabetes care. Front. Digit. Health 8:1685842. doi: 10.3389/fdgth.2026.1685842
DOI: 10.17632/j26gdxcw7f.1
title: Type 2 Diabetes Mellitus Real-World Data Preprocessing and Modeling

description: Machine Learning (ML) applied to healthcare Real World Data (RWD) may improve patient management. RWD, however, requires extensive preprocessing to make it ML-ready. The aim of this resource is to explore the impact of preprocessing on ML models applied to RWD from type 2 diabetes patients visits. A GitHub repo is available with the code related to the experiments, to show all the steps we prepared, the decisions we took and alternative pipelines we created.

Work done in partial fulfillment of my PhD dissertation: "Leveraging real-world data with machine learning to disentangle the complexity of multimorbid internal medicine patients"

Linked in the paper: Montagna M, Rabadzhiev AS, Traverso A, Setola E, Draetta E, Dimonte A, Barbieri S, Fabiani B, Piemonti L, Esposito A, Tacchetti C and Rovere Querini P (2026) From raw data to actionable insights: preprocessing real-world data for machine learning in diabetes care. Front. Digit. Health 8:1685842. doi: 10.3389/fdgth.2026.1685842
DOI: 10.15468/dl.wwvw5b
title: Occurrence Download

description: A dataset containing 224663 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 Spergula"
 ]
}

 The dataset includes 224663 records from 1423 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009937-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e3a6y8
title: Occurrence Download

description: A dataset containing 3678765 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-0.35494 44.43576,1.04739 44.29186,1.70771 44.28517,1.79434 44.77298,1.41359 45.6985,-0.30733 45.40617,-0.35494 44.43576))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 3678765 records from 2997 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007549-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5519/qd.6r1htujw
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (75084 records)
DOI: 10.15468/dl.m2mhgs
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eurypygiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-160 -40,-150 -40,-150 -30,-160 -30,-160 -40))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018744-251009101135966/datasets/export for details.
DOI: 10.5281/zenodo.15608222
title: Cases data and high quality figures of "OpenBench: a land models evaluation system"

description: This dataset contains Openbench drawing data and the necessary data files required to generate the drawing, also includes relevant files generated by Openbench processing.
DOI: 10.5281/zenodo.15064054
title: Cases data and high quality figures of "OpenBench: a land models evaluation system"

description: This dataset contains Openbench drawing data and the necessary data files required to generate the drawing, also includes relevant files generated by Openbench processing.
DOI: 10.17632/g727dxrdwk.1
title: LINF_190012700

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/rb4rjfhzp5.1
title: LINF_190012400

description: Arsenite methyltransferase-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.3535/bh6-vt0-yxz
title: Parasacculina

description: Digital Specimen for the physical specimen hosted at Senckenberg Research Institute and Natural History Museum Frankfurt/M.
DOI: 10.15468/dl.g92g2d
title: Occurrence Download

description: A dataset containing 154785 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Anhinga rufa)",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 154785 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0077973-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9hg7hr
title: Occurrence Download

description: A dataset containing 227258 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Alisterus scapularis)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 227258 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0077969-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.539tuz
title: Occurrence Download

description: A dataset containing 2088 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tinca tinca",
 "Country is Norway",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2088 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078005-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18672237
title: SHUKUR XOLMIRZAYEV ASARLARIDA OG'ZAKI NUTQ LEKSIKASI VA OKKAZIONAL SO'ZLARNING STILISTIK FUNKSIYASI

description: Maqolada Shukur Xolmirzayevning “Og‘ir tosh ko‘chsa” hikoyasi va “So‘nggi bekat” romani og‘zaki nutq leksikasi hamda okkazional so‘zlarning stilistik vazifasi jihatidan tadqiq etiladi. Tadqiqotda yozuvchi asarlarida qo‘llangan dialektizmlar, so‘z yasash usullari va individual uslubiy xususiyatlar tahlil qilingan. Og‘zaki nutqqa xos lug‘aviy vositalarning emotsional-ekspressiv ma‘nolar yaratishdagi roli, okkazional yasalmalarning semantik imkoniyatlari va ularning badiiy tasvirni boyitishdagi ahamiyati asoslab berildi. Yozuvchining affiks va prefikslardan mahorat bilan foydalanib yangi ma‘noli birliklar yaratish mahorati ko‘rsatilgan. Asarlardagi til birliklari matn kontekstida tekshirilgan va ularning badiiy-estetik funksiyasi ochib berilgan.
DOI: 10.5281/zenodo.18672238
title: SHUKUR XOLMIRZAYEV ASARLARIDA OG'ZAKI NUTQ LEKSIKASI VA OKKAZIONAL SO'ZLARNING STILISTIK FUNKSIYASI

description: Maqolada Shukur Xolmirzayevning “Og‘ir tosh ko‘chsa” hikoyasi va “So‘nggi bekat” romani og‘zaki nutq leksikasi hamda okkazional so‘zlarning stilistik vazifasi jihatidan tadqiq etiladi. Tadqiqotda yozuvchi asarlarida qo‘llangan dialektizmlar, so‘z yasash usullari va individual uslubiy xususiyatlar tahlil qilingan. Og‘zaki nutqqa xos lug‘aviy vositalarning emotsional-ekspressiv ma‘nolar yaratishdagi roli, okkazional yasalmalarning semantik imkoniyatlari va ularning badiiy tasvirni boyitishdagi ahamiyati asoslab berildi. Yozuvchining affiks va prefikslardan mahorat bilan foydalanib yangi ma‘noli birliklar yaratish mahorati ko‘rsatilgan. Asarlardagi til birliklari matn kontekstida tekshirilgan va ularning badiiy-estetik funksiyasi ochib berilgan.
DOI: 10.26193/t9i8gk
title: Wave 2 of the Longitudinal Survey of Retrenched Automotive Workers
title: Stream 1 Longitudinal Workers Survey

description: This dataset presents the results of the Wave 2 of the Longitudinal Workers Survey of Retrenched Workers. Participants in our longitudinal workers survey had jobs which were earmarked for retrenchment leading up to the closure of assembly plants operated in Australia by General Motors Holden, Toyota Motor Company, and Ford. Participant contact information was passed on to the research team at the University of South Australia by the government partners of the project. Participants had provided consent for their details to be used for further communication as part of their engagement in retraining and transition services. All participants in Wave 2 had participated in the Wave 1 survey.

The study was developed to investigate the efficacy of private and public investments in pre-retrenchment counselling and training, by collecting data to help understand:

- Which factors affect decisions to exit or stay in the labour market;
- Which factors improve the chances of employment;
- Which factors shorten the spell of unemployment; and
- The intermittency of work careers and labour ‘branching’ processes.
description: Longitudinal Workers Survey of Retrenched Automotive Workers
description: Yet to be published.
DOI: 10.15156/bio/sh1407574.10fu
title: SH1407574.10FU

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/sh1407578.10fu
title: SH1407578.10FU

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/sh1407579.10fu
title: SH1407579.10FU

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/sh1407582.10fu
title: SH1407582.10FU

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/sh1407590.10fu
title: SH1407590.10FU

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.