cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.m3qauy
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((13.27572 55.68802, 13.31529 55.64814, 13.34814 55.63626, 13.3529 55.61776, 13.33232 55.61229, 13.31542 55.62221, 13.30362 55.60639, 13.34314 55.55803, 13.36993 55.56285, 13.39246 55.53391, 13.45003 55.52777, 13.47397 55.52692, 13.48892 55.54821, 13.49454 55.57524, 13.51832 55.58236, 13.54047 55.63272, 13.59667 55.63678, 13.60329 55.65271, 13.61363 55.66865, 13.5608 55.69821, 13.52745 55.70303, 13.45895 55.73272, 13.42704 55.73407, 13.38381 55.74697, 13.32742 55.75445, 13.29833 55.75102, 13.30294 55.76854, 13.28785 55.78057, 13.25218 55.77391, 13.22762 55.79063, 13.21336 55.79196, 13.14345 55.78734, 13.13535 55.74825, 13.12902 55.72418, 13.11222 55.71342, 13.11544 55.70357, 13.14513 55.70636, 13.17349 55.68175, 13.20437 55.69265, 13.21293 55.67843, 13.27572 55.68802))",
 "ScientificName is one of (Lycaenidae, Hesperiidae, Nymphalidae, Papilionidae, Pieridae, Riodinidae, Zygaenidae)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2023",
 "BasisOfRecord is Human Observation",
 "Country is Sweden",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020747-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2kbbnx
title: CCDC 2363429: Experimental Crystal Structure Determination

description: Related Article: Chuanhui Liu, Wenzheng Feng, Shaofeng Liu, Ze Kan, Zhibo Li|2024|Inorg.Chem.|63|19676|doi:10.1021/acs.inorgchem.4c02857
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2kbbpy
title: CCDC 2363430: Experimental Crystal Structure Determination

description: Related Article: Chuanhui Liu, Wenzheng Feng, Shaofeng Liu, Ze Kan, Zhibo Li|2024|Inorg.Chem.|63|19676|doi:10.1021/acs.inorgchem.4c02857
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2kc0rq
title: CCDC 2364083: Experimental Crystal Structure Determination

description: Related Article: Vijay Kumar Mandal, Kumar Gaurav, Sandeep H. Kaulage, Shabana Khan|2024|Inorg.Chem.|63|20510|doi:10.1021/acs.inorgchem.4c03114
description: Related Article: Vijay Kumar Mandal|2024|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2kgqzr
title: CSD 2367655: Experimental Crystal Structure Determination

description: Related Article: Igor Plokhikh|2024|CSD Communication|||
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.21410/7e4/jy3nyn/fvdckp
title: fr_cdsp_ddi_enef2017_v14.tab

description: :unav
DOI: 10.21410/7e4/jy3nyn/j1zsnz
title: Questionnaire_ENEF2017_V14.docx

description: :unav
DOI: 10.21410/7e4/jy3nyn/lxp4wr
title: Documentation_ENEF2017_V14.pdf

description: :unav
DOI: 10.21410/7e4/jy3nyn
title: Enquête électorale française 2017 (ENEF 2017), Vague 14

description: Ce dispositif de suivi et de mesure de l’opinion permet l’analyse des évolutions de l’électorat français et de ses réactions aux événements politiques, sociaux et économiques à travers 20 vagues, depuis la veille des élections régionales de 2015 jusqu’au lendemain des élections législatives de 2017. Il permet des analyses détaillées au niveau national et régional pour saisir les évolutions de l’opinion articulées au contexte spécifique de la période préélectorale, électorale et postélectorale. Il fournit une série d’indicateurs et de mesures sur les tendances de l’électorat français, ses valeurs politiques, ses préférences partisanes, son rapport au vote et aux candidats. L'enquête détaille les ressorts psychologiques de la décision électorale à la lumière des valeurs des Français et des contextes politiques, géographiques et socio-économiques. Elle met également en évidence l’articulation entre le niveau national et le niveau local dans les caractéristiques de l’opinion. Enfin, la réception par l’opinion des thèmes inscrits à l’agenda politique par les candidats est une dimension importante, notamment pendant la période de campagne (Primaires, élection présidentielle, élections législatives). Cette quatorzième vague, menée en avril-mai 2017, était réalisée entre le premier et le second tour de l'élection présidentielle. Elle visait à évaluer l'action du Président de la République, l'abstention et le vote blanc au premier tour, le second tour ainsi que l'image des candidats, entre autres sujets ; 15 807 personnes inscrites sur les listes électorales y ont participé.
DOI: 10.21410/7e4/jy3nyn/esrnzd
title: fr_cdsp_ddi_enef2017_v14.tab

description: :unav
DOI: 10.21410/7e4/jy3nyn/kq3l5s
title: Documentation_ENEF2017_V14.pdf

description: :unav
DOI: 10.21410/7e4/jy3nyn/umdsxg
title: fr_cdsp_ddi_enef2017_v14_sas.zip

description: :unav
DOI: 10.21410/7e4/jy3nyn/yrgxsx
title: fr_cdsp_ddi_enef2017_v14.xml

description: :unav
DOI: 10.21410/7e4/jy3nyn/zkglzy
title: fr_cdsp_ddi_enef2017_v14-1.tab

description: :unav
DOI: 10.5517/ccdc.csd.cc2kp2x8
title: CCDC 2373760: Experimental Crystal Structure Determination

description: Related Article: Ramkumar Kannan, Anna Chandrasekar Murali, Krishnan Venkatasubbaiah, Vadapalli Chandrasekhar|2024|Inorg.Chem.|63|19561|doi:10.1021/acs.inorgchem.4c02342
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2kp2y9
title: CCDC 2373761: Experimental Crystal Structure Determination

description: Related Article: Ramkumar Kannan, Anna Chandrasekar Murali, Krishnan Venkatasubbaiah, Vadapalli Chandrasekhar|2024|Inorg.Chem.|63|19561|doi:10.1021/acs.inorgchem.4c02342
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.21410/7e4/tgki82/7mzcqv
title: Documentation_ENEF2017_V15.pdf

description: :unav
DOI: 10.21410/7e4/tgki82/lbr0hv
title: fr_cdsp_ddi_enef2017_v15-1.tab

description: :unav
DOI: 10.21410/7e4/tgki82
title: Enquête électorale française 2017 (ENEF 2017), Vague 15

description: Ce dispositif de suivi et de mesure de l’opinion permet l’analyse des évolutions de l’électorat français et de ses réactions aux événements politiques, sociaux et économiques à travers 20 vagues, depuis la veille des élections régionales de 2015 jusqu’au lendemain des élections législatives de 2017. Il permet des analyses détaillées au niveau national et régional pour saisir les évolutions de l’opinion articulées au contexte spécifique de la période préélectorale, électorale et postélectorale. Il fournit une série d’indicateurs et de mesures sur les tendances de l’électorat français, ses valeurs politiques, ses préférences partisanes, son rapport au vote et aux candidats. L'enquête détaille les ressorts psychologiques de la décision électorale à la lumière des valeurs des Français et des contextes politiques, géographiques et socio-économiques. Elle met également en évidence l’articulation entre le niveau national et le niveau local dans les caractéristiques de l’opinion. Enfin, la réception par l’opinion des thèmes inscrits à l’agenda politique par les candidats est une dimension importante, notamment pendant la période de campagne (Primaires, élection présidentielle, élections législatives). Cette quinzième vague, menée à la fin de mai 2017, était la première réalisée après le second tour de l'élection présidentielle. Elle visait à évaluer l'action du Président de la République et du Premier Ministre, l’intérêt pour les élections législatives, l’image des représentants des différentes forces politiques et le potentiel électoral des partis politiques, entre autres sujets ; 15 493 personnes inscrites sur les listes électorales y ont participé.
DOI: 10.21410/7e4/tgki82/4aem9m
title: Questionnaire_ENEF2017_V15.docx

description: :unav
DOI: 10.21410/7e4/tgki82/lzghaq
title: fr_cdsp_ddi_enef2017_v15.tab

description: :unav
DOI: 10.21410/7e4/tgki82/pu7ycs
title: RapportTechnique_ENEF2017_V15.pdf

description: :unav
DOI: 10.21410/7e4/tgki82/tvqju0
title: fr_cdsp_ddi_enef2017_v15_csv.zip

description: :unav
DOI: 10.21410/7e4/tgki82/vqleu5
title: fr_cdsp_ddi_enef2017_v15.xml

description: :unav
DOI: 10.21410/7e4/tgki82/ykqhuz
title: fr_cdsp_ddi_enef2017_v15_sas.zip

description: :unav
DOI: 10.17632/tyh2hpg3h9
title: The Influence of Social Media Design, Promotion Tools, and Product Quality on Service Marketing Performance in the Digital Economy Data

description: The Influence of Social Media Design, Promotion Tools, and Product Quality on Service Marketing Performance in the Digital Economy Data
DOI: 10.17632/tyh2hpg3h9.1
title: The Influence of Social Media Design, Promotion Tools, and Product Quality on Service Marketing Performance in the Digital Economy Data

description: The Influence of Social Media Design, Promotion Tools, and Product Quality on Service Marketing Performance in the Digital Economy Data
DOI: 10.7916/ypkn-x736
title:  Data for: Scaling of moored surface ocean turbulence measurements in the Southeast Pacific Ocean
DOI: 10.17632/rmtfz6y2fj
title: Meta-analysis Data on Working Memory in Mathematical Difficulty

description: This repository contains the raw and coded data used in the meta-analysis examining the relationship between working memory and mathematical difficulties in children. The dataset includes study identifiers, effect sizes, sample sizes, working memory measures, and references to the original publications. All data were extracted from peer-reviewed studies and are fully anonymized at the study level.
DOI: 10.17632/rmtfz6y2fj.1
title: Meta-analysis Data on Working Memory in Mathematical Difficulty

description: This repository contains the raw and coded data used in the meta-analysis examining the relationship between working memory and mathematical difficulties in children. The dataset includes study identifiers, effect sizes, sample sizes, working memory measures, and references to the original publications. All data were extracted from peer-reviewed studies and are fully anonymized at the study level.
DOI: 10.15468/dl.jqnc2q
title: Occurrence Download

description: A dataset containing 283 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Polypodium niponicum)"
 ]
}

 The dataset includes 283 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009798-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/d7j5wvc5v5
title: bias_undergraduates_210925

description: This database shows the levels of financial biases and competencies of 403 first- and fourth-year university students. Fieldwork was conducted in September 2023 using a structured questionnaire.
DOI: 10.17632/d7j5wvc5v5.1
title: bias_undergraduates_210925

description: This database shows the levels of financial biases and competencies of 403 first- and fourth-year university students. Fieldwork was conducted in September 2023 using a structured questionnaire.
DOI: 10.17632/h4gcfmbk5c.1
title: Dataset of GenAI Preference and Digital Citizenship Multidimentional

description: This dataset presents information on generative artificial intelligence (GenAI) preferences and multidimensional digital citizenship among 2008 prospective civic education teachers in Indonesia. Data were collected through a online survey covering demographic profiles (gender, year of study, parental education, and occupation), types and purposes of GenAI usage, and validated measures of digital citizenship across four sub-dimensions: digital inclusion, ethics, civility, and civic engagement. Additional variables include self-efficacy and concerns related to GenAI use, providing a comprehensive view of how emerging technologies intersect with civic competencies in higher education. Structured for reproducibility and potential reuse, this dataset can support cross-regional comparisons, longitudinal extensions, and alternative analytical approaches. It provides researchers, educators, and policymakers with empirical evidence to inform theoretical developments, comparative studies, and policy design on digital citizenship and the responsible use of generative AI in education.
DOI: 10.7916/kp8r-g741
title:  Data for: Scaling the Bubble Penetration Depth in the Ocean
DOI: 10.17632/pyhd85vf4p
title: Evaluation of Green Investment in Solar Photovoltaic Power Plants Using Analytical Hierarchy Process in Archipelago

description: This study evaluates green investment in solar photovoltaic (PV) power plants in Indonesia’s archipelago using the Analytical Hierarchy Process (AHP). Despite the national renewable energy (RE) target of 23% by 2025, the development of wind and solar projects remains constrained by high investment risks, inadequate infrastructure, and regulatory uncertainties. As an archipelagic country with abundant solar resources, Indonesia faces the dual challenge of mobilizing sustainable financing while reducing reliance on fossil-fuel-based diesel plants. The research aims to identify and prioritize determinants influencing green investment decision-making for solar PV in archipelago. Data were gathered through structured questionnaires and interviews with 75 respondents, of which 35 responses met the AHP consistency ratio requirement. The four-level hierarchical model reveals that policy factors (0.4825) exert the strongest influence, followed by economic (0.3120) and technical (0.2055) factors. At the sub-criteria level, profitability (0.7724), renewables obligation (0.6055), and technological maturity (0.6020) rank highest, highlighting the role of financial viability, regulatory enforcement, and proven technology in shaping investment attractiveness. The findings show policymakers favor short-term fiscal support, whereas researchers and practitioners stress long-term regulatory certainty and financing accessibility. The study’s novelty lies in integrating multi-stakeholder perspectives into a structured model, offering quantitative insights for green finance strategies.
DOI: 10.17632/pyhd85vf4p.1
title: Evaluation of Green Investment in Solar Photovoltaic Power Plants Using Analytical Hierarchy Process in Archipelago

description: This study evaluates green investment in solar photovoltaic (PV) power plants in Indonesia’s archipelago using the Analytical Hierarchy Process (AHP). Despite the national renewable energy (RE) target of 23% by 2025, the development of wind and solar projects remains constrained by high investment risks, inadequate infrastructure, and regulatory uncertainties. As an archipelagic country with abundant solar resources, Indonesia faces the dual challenge of mobilizing sustainable financing while reducing reliance on fossil-fuel-based diesel plants. The research aims to identify and prioritize determinants influencing green investment decision-making for solar PV in archipelago. Data were gathered through structured questionnaires and interviews with 75 respondents, of which 35 responses met the AHP consistency ratio requirement. The four-level hierarchical model reveals that policy factors (0.4825) exert the strongest influence, followed by economic (0.3120) and technical (0.2055) factors. At the sub-criteria level, profitability (0.7724), renewables obligation (0.6055), and technological maturity (0.6020) rank highest, highlighting the role of financial viability, regulatory enforcement, and proven technology in shaping investment attractiveness. The findings show policymakers favor short-term fiscal support, whereas researchers and practitioners stress long-term regulatory certainty and financing accessibility. The study’s novelty lies in integrating multi-stakeholder perspectives into a structured model, offering quantitative insights for green finance strategies.
DOI: 10.17632/tzc92phtg4
title: Schizophrenia GWAS

description: This file provides summary statistics from a schizophrenia genome-wide association study (GWAS) conducted in a Brazilian population. It includes SNP chromosome and position, odds ratios, p-values, allele frequencies, and other relevant metrics.
DOI: 10.17632/tzc92phtg4.2
title: Schizophrenia GWAS

description: This file provides summary statistics from a schizophrenia genome-wide association study (GWAS) conducted in a Brazilian population. It includes SNP chromosome and position, odds ratios, p-values, allele frequencies, and other relevant metrics.
DOI: 10.15468/dl.44hhc5
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dysphania cristata",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 13 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009800-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4cj86a
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dysphania cristata",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009801-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7916/d8hq56zv
title:  Data for: Spectral characteristics of gravity-capillary waves, with connections to wave growth and microbreaking

description: In order to improve our understanding of physical air-sea interaction, it is essential to better describe the short-scale ocean wave response to wind forcing. This is particularly true for waves which are small enough to evade observation by traditional buoy and point-based gauge measurements but large enough to appreciably alter the transfer of momentum between atmosphere and ocean. Such waves are restored to equilibrium both by the earth’s gravity and air-sea surface tension, hence the classification as “gravity-capillary”. Radar remote sensing techniques depend greatly upon these waves in order to extract useful physical parameters from afar. Despite this importance, field observations of gravity-capillary wave characteristics are uncommon and vary from study to study. Furthermore, leading-edge model wavenumber spectra generally do not match each other in shape or important spectral parameters. Here we present an extended analysis of short wave data collected via a polarimetric camera aboard Research Platform (R/P) FLoating Instrument Platform (FLIP) in the Santa Barbara Channel. Our wavenumber saturation spectra show the emergence of a peak in the gravity-capillary subrange at low wind forcing magnitude (u*~0.045 m/s), consistent with critical wave growth in air-side stability theory. This is accompanied by a sharp increase in gravity-capillary-scale wave slope variance, a phenomenon that was previously only observed in the laboratory. Finally, the effects of microbreaking on wave spectral characteristics are discussed.
DOI: 10.17632/rk343v5jk4
title: Demand Disagreement Part C

description: This contains the consumption share distribution used in the online appendix for the paper "Demand Disagreement" by Christian Heyerdahl-Larsen and Philipp Illeditsch.
DOI: 10.17632/rk343v5jk4.1
title: Demand Disagreement Part C

description: This contains the consumption share distribution used in the online appendix for the paper "Demand Disagreement" by Christian Heyerdahl-Larsen and Philipp Illeditsch.
DOI: 10.17632/md24pnhz67
title: Demand Disagreement Part B

description: This is Part B of the dataset for the paper “Demand Disagreement” by Christian Heyerdahl-Larsen and Philipp Illeditsch. It contains the H5 files.
DOI: 10.17632/md24pnhz67.1
title: Demand Disagreement Part B

description: This is Part B of the dataset for the paper “Demand Disagreement” by Christian Heyerdahl-Larsen and Philipp Illeditsch. It contains the H5 files.
DOI: 10.17632/5vpb5rzv7s.1
title: Demand Disagreement Data Part A

description: This data is for the paper "Demand Disagreement" by Christian Heyerdahl-Larsen and Philipp Illeditsch. For details, please see the attached README file. The data in split into two different repositories. This is Part A. The other part B is in Demand Disagreement Data Part A
DOI: 10.15468/dl.2tbkg4
title: Occurrence Download

description: A dataset containing 56041 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix fragilis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 56041 records from 777 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009742-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7916/d8-zqp3-fn39
title:  Data for: The impact of wind gusts on the ocean thermal skin layer

description: Data used for the analysis described in "The Impact of Wind Gusts on the Ocean Thermal Skin Layer" by Zappa et al. [2019], Geophysical Research Letters (DOI: 10.1002/2019GL083687) Contents: water surface and sky brightness temperature, wind speed/stress, and mean gust/thermal front propagation speeds. README file within archive provides breakdown of all constituent elements.