cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2npp9c
title: CCDC 2463703: Experimental Crystal Structure Determination

description: Related Article: Keishi Yamabayashi, Kai Okazaki, Daisuke Nakauchi, Shohei Katao, Junko Kamikubo, Takumi Kato, Noriaki Kawaguchi, Takayuki Yanagida|2025|J.Mater.Chem.C|13|23562|doi:10.1039/d5tc02970h
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.cc2npx8k
title: CCDC 2463919: Experimental Crystal Structure Determination

description: Related Article: Hannah M. Hansen, Joshua C. Zgrabik, Peter A. Zacher, Jacob J. Schuely, Emily M. Amano, Mai Yer Yang, Daniel K. Unruh, Lucia Zuin, Jason M. Keith, Scott R. Daly|2025|Chemical Science|16|22333|doi:10.1039/d5sc06254c
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.cc2npx9l
title: CCDC 2463920: Experimental Crystal Structure Determination

description: Related Article: Hannah M. Hansen, Joshua C. Zgrabik, Peter A. Zacher, Jacob J. Schuely, Emily M. Amano, Mai Yer Yang, Daniel K. Unruh, Lucia Zuin, Jason M. Keith, Scott R. Daly|2025|Chemical Science|16|22333|doi:10.1039/d5sc06254c
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.cc2npxbm
title: CCDC 2463921: Experimental Crystal Structure Determination

description: Related Article: Hannah M. Hansen, Joshua C. Zgrabik, Peter A. Zacher, Jacob J. Schuely, Emily M. Amano, Mai Yer Yang, Daniel K. Unruh, Lucia Zuin, Jason M. Keith, Scott R. Daly|2025|Chemical Science|16|22333|doi:10.1039/d5sc06254c
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.cc2npxcn
title: CCDC 2463922: Experimental Crystal Structure Determination

description: Related Article: Hannah M. Hansen, Joshua C. Zgrabik, Peter A. Zacher, Jacob J. Schuely, Emily M. Amano, Mai Yer Yang, Daniel K. Unruh, Lucia Zuin, Jason M. Keith, Scott R. Daly|2025|Chemical Science|16|22333|doi:10.1039/d5sc06254c
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: 10.17632/yjmdhjnwx7.3
title: Remittance inflows, democracy and economic freedom in developing countries: An approach based on democratic regimes

description: Replication Package Paper Title:
 Remittance inflows, democracy and economic freedom in developing countries: An approach based on democratic regimes
Authors: 
Relwendé SAWADOGO ( Université Joseph KI-ZERBO, Burkina Faso)
Gervasio SEMEDO ( Université de Tours , Frnace)
Pousseni BAKOUAN ( Université Virtuelle du Burkina )
 Date: December 9, 2025 
1. Overview 
This replication package provides all the publicly available data, code, and instructions required to reproduce the main empirical results of the above-mentioned research paper. The package is designed to facilitate transparency and enable independent verification of all statistical findings reported in the study.
DOI: 10.17632/82mtzd8x72.1
title: Multi-Class Brain Tumor MRI Dataset: Glioma, Healthy Brain, Meningioma, and Pituitary Macroadenoma

description: This dataset presents a high-quality collection of brain MRI images categorized into four clinically relevant classes: Glioma, Meningioma, Pituitary Macroadenoma, and Healthy brain scans. Each category contains 300 images, resulting in a balanced dataset of 1,200 images suitable for robust machine learning, deep learning, and radiological analysis.

All MRI images have been collected from verified medical sources and anonymized to ensure ethical compliance. A verification certificate is included to validate the authenticity and approved use of the dataset. The images capture diverse tumor characteristics, sizes, and anatomical variations, providing a comprehensive resource for academic and clinical research.

This dataset is intended to support a range of applications, including but not limited to: brain tumor classification, tumor detection, segmentation research, radiomics analysis, and AI-driven medical imaging model development. Its balanced class distribution and clear labeling make it particularly useful for training supervised learning models.
DOI: 10.17632/ckpxd8xx22.1
title: Dynamic regulation of neuronal vault trafficking and RNA cargo by the noncoding RNA, Vaultrc5

description: Vaults are large ribonucleoprotein complexes of unknown function. Here, we report that the vault-associated noncoding RNA, Vaultrc5, is highly enriched at the synapse and is required for activity-dependent vault trafficking in primary cortical neurons. We have discovered that vaults are comprised of unique populations of coding and non-coding RNA, and that this cargo varies dynamically between subcellular compartments. In addition, Vaultrc5 knockdown at the synapse shifts the RNA cargo toward transcripts associated with immune surveillance, and Vaultrc5 knockdown, in vivo, leads to impaired fear learning. These findings suggest that the Vaultrc5 is critically involved in coordinating the experience-dependent trafficking of vaults and related RNA cargo, which represents a novel feature of neuronal plasticity underlying learning and memory.
DOI: 10.17632/x957x8fn3y.1
title: Dataset for Hybrid Experimental–Computational Analysis of Head and Neck Injury Biomechanics on Sand and Artificial Turf Surfaces
DOI: 10.17632/m3ffn9thjg.1
title: natural isotope data in long-term fertilized grassland

description: Soil chemical properties and natural isotopes values in fertilized topsoil and subsoil
DOI: 10.17632/dh8nj2dvhr
title: Toxicity of tetrabromobisphenol A to human thyroid follicular epithelial cells through oxidative stress: A combined analysis at the cellular and molecular levels

description: Original data
DOI: 10.17632/dh8nj2dvhr.2
title: Toxicity of tetrabromobisphenol A to human thyroid follicular epithelial cells through oxidative stress: A combined analysis at the cellular and molecular levels

description: Original data
DOI: 10.17632/s9n5h4xjzd
title: Executive Function and Sensory Processing in ASD and Epilepsy

description: This anonymized dataset contains the raw data used for the analyses reported in the manuscript titled “Executive Function and Sensory Processing in a Population with Autism Spectrum Disorder and Epilepsy: A Comparative Empirical Study.”
It includes variables related to executive functioning (BRIEF-2, ENFEN), sensory processing (SP-2), diagnostic group (ASD, Epilepsy, ASD+Epilepsy), and relevant sociodemographic and clinical covariates.
All identifying information has been removed to ensure confidentiality. The dataset is provided exclusively for peer-review purposes.
DOI: 10.17632/s9n5h4xjzd.1
title: Executive Function and Sensory Processing in ASD and Epilepsy

description: This anonymized dataset contains the raw data used for the analyses reported in the manuscript titled “Executive Function and Sensory Processing in a Population with Autism Spectrum Disorder and Epilepsy: A Comparative Empirical Study.”
It includes variables related to executive functioning (BRIEF-2, ENFEN), sensory processing (SP-2), diagnostic group (ASD, Epilepsy, ASD+Epilepsy), and relevant sociodemographic and clinical covariates.
All identifying information has been removed to ensure confidentiality. The dataset is provided exclusively for peer-review purposes.
DOI: 10.15468/dl.sedgct
title: Occurrence Download

description: A dataset containing 15643 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is FRA.4_1",
 "License is one of (CC-BY 4.0, CC0 1.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Linaria cannabina",
 "Year 2000-2025"
 ]
}

 The dataset includes 15643 records from 322 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045232-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/gfjt3m2r6n.2
title: Who Wants to 'Japa' and Why?: Dataset on Migration Decisions of Nigerian Youth

description: This dataset presents data collected through two surveys: the first among staff and students of 3 universities in Osun State, Nigeria; and the second among intending and serving Corps members as well as those who recently concluded their NYSC (National Youth Service Corps) service year. The first survey was administered in July 2024, and the second one between November 2024 and October 2025. The surveys were collected with the use of online questionnaires. The questionnaires are similar, the second survey containing a few additional questions than the first survey. The cleaned and merged dataset contains 835 observations. 

The surveys sought to understand migration aspirations and perspectives, as well as correlates of migration decisions among Nigerian youth. The surveys were also intended to determine the relationship between developmental idealism and migration within the context of the gripping novel intensity, urgency and desperation by which Nigerian youth move to other countries - a phenomenon that has come to be known colloquially as 'japa'. The dataset captures self-reported migration intentions and related socio-demographic, economic and attitudinal covariates among young Nigerians. Researchers studying migration decision-making, labour market aspirations, views about development of Nigeria in comparison with other countries, and the drivers of irregular and regular migration will find the data useful.
DOI: 10.17632/yfywfwp7yr
title: Mobility transition in the automotive industry in Germany and Japan: A patent network analysis (data and graphs)

description: Patent documents offer insights into the countries dedicating resources to specific technologies, enabling the identification of potential innovation trends, particularly emerging technologies, and the development of innovation capabilities. International Patent Classification (IPC) codes are assigned to patents, much like keywords are assigned to scientific articles. For this study, two IPC code co-occurrence networks are constructed. Both IPC co-occurrence networks are undirected and consist of nodes (IPC codes) and weighted edges (the number of times IPC codes co-occur). IPC codes are co-occurring if they are assigned to the same patent. Codes are included in the analysis if they occur at least two times and are part of the largest connected component of the network. 

The networks are based on the patent data of the leading Japanese and German car manufacturers. The main search query (223,688 patents) is narrowed down to patents with application dates from 2012 to 2023 (183,706). The Japanese dataset (9,685 patents) limits the main query to the three largest Japanese car manufacturers: Honda, Nissan, and Toyota (including subsidiaries: Daihatsu and Hino). The German dataset (1,381 patents) limits the main query to the three largest German car manufacturers: BMW, Mercedes-Benz, and Volkswagen (including subsidiaries: Audi and Porsche). The patent data are downloaded from the PATENTSCOPE database of the World Intellectual Property Organization. For network analysis, we use Gephi and VOSviewer. The PATENTSCOPE data are imported into VOSviewer and formatted as co-occurrence networks. Gephi is used to calculate diameter-based centrality and modularity class. The graph layout is ForceAtlas2.
DOI: 10.17632/yfywfwp7yr.1
title: Mobility transition in the automotive industry in Germany and Japan: A patent network analysis (data and graphs)

description: Patent documents offer insights into the countries dedicating resources to specific technologies, enabling the identification of potential innovation trends, particularly emerging technologies, and the development of innovation capabilities. International Patent Classification (IPC) codes are assigned to patents, much like keywords are assigned to scientific articles. For this study, two IPC code co-occurrence networks are constructed. Both IPC co-occurrence networks are undirected and consist of nodes (IPC codes) and weighted edges (the number of times IPC codes co-occur). IPC codes are co-occurring if they are assigned to the same patent. Codes are included in the analysis if they occur at least two times and are part of the largest connected component of the network. 

The networks are based on the patent data of the leading Japanese and German car manufacturers. The main search query (223,688 patents) is narrowed down to patents with application dates from 2012 to 2023 (183,706). The Japanese dataset (9,685 patents) limits the main query to the three largest Japanese car manufacturers: Honda, Nissan, and Toyota (including subsidiaries: Daihatsu and Hino). The German dataset (1,381 patents) limits the main query to the three largest German car manufacturers: BMW, Mercedes-Benz, and Volkswagen (including subsidiaries: Audi and Porsche). The patent data are downloaded from the PATENTSCOPE database of the World Intellectual Property Organization. For network analysis, we use Gephi and VOSviewer. The PATENTSCOPE data are imported into VOSviewer and formatted as co-occurrence networks. Gephi is used to calculate diameter-based centrality and modularity class. The graph layout is ForceAtlas2.
DOI: 10.17632/wggpwmb29r
title: Dramatically Enhancing the Flexural Stiffness of Addictive Manufactured Metallic Lattice Structures via Ultrathin Skin Wrapping

description: Dataset for "Dramatically Enhancing the Flexural Stiffness of Addictive Manufactured Metallic Lattice Structures via Ultrathin Skin Wrapping"
DOI: 10.17632/wggpwmb29r.1
title: Dramatically Enhancing the Flexural Stiffness of Addictive Manufactured Metallic Lattice Structures via Ultrathin Skin Wrapping

description: Dataset for "Dramatically Enhancing the Flexural Stiffness of Addictive Manufactured Metallic Lattice Structures via Ultrathin Skin Wrapping"
DOI: 10.17632/bjkct6pwx5.1
title: Raman Analysis of WS2 Modes in an Epoxy Matrix
DOI: 10.5281/zenodo.17883090
title: Friction coefficient of cushion vinyl floorings

description: Determination of the friction coefficient of cushion vinyl floorings having different reliefs in the base layer (ID23)
DOI: 10.17632/pwffhg6nhz
title: IndiaScene365
DOI: 10.17632/pwffhg6nhz.1
title: IndiaScene365
DOI: 10.17632/9v349h653n
title: Flood risk assessment along the River Niger

description: The dataset used to build a novel Flood Risk Assessment (FRA) for semi-arid rural areas is provided here. Our FRA aims to address the recurring shortcomings in multi-hazard, participation, and risk reduction in the FRA for semi-arid rural regions published over the last decade.
We hypothesise that assessing flood risk by integrating high-resolution geoinformation and local knowledge in a participatory process enables the identification of risk reduction measures, thereby contributing to flood risk assessment in risk management.
Data show the flood-prone area of the River Niger upstream of the city of Niamey during local and Guinean floods, each with three probabilities of occurrence (return periods of 10, 30, and 100 years). Moreover, the data include the basin of the Karma Wadi (the largest tributary of the Niger River, which is reported to flood crops along the River Niger) and the highlands requiring treatment. Further information in the dataset includes assets exposed to each flood, expected damage, risk levels for each of the five municipalities along the river, potential risk-reduction measures, and their cost-benefit analyses.
The main findings of the FRA are: 
1) River flooding during the dry season causes more damage than during the wet season
2) Expected damage to irrigated crops is greater than damage to buildings
3) High-resolution geoinformation and local knowledge identify a feasible risk reduction
4) Raising the levees of rice fields, hygiene, and sanitation are priorities
5) High land prices hinder resettlement and redirect land development
The data consists of an Excel file reporting (i) crops, settlements, buildings (footprint and number) exposed to 6 flood scenarios organised by municipality; (ii) expected damage, (iii) SWOT analysis on measures; (iv) Measures priority; (v) Risk reduction; (vi) Cost-benefit analysis. Moreover, five folders contain shape files of flood-prone areas, categorised by six scenarios (two types of floods and three probabilities of occurrence each), water depth, and assets (crops and buildings). Finally, two figures in PNG format localise each flood-prone settlement mentioned in the tables.
Data were gathered from daily river discharge data provided by the Ministry of Hydraulics and Sanitation of Niger, a digital elevation model extracted from Planet satellite images and land cover Google Earth images of February 2024, the Information System on Rural Markets (SIMA), field inspections on February 2025, and focus groups conducted with the municipalities of Gothèye, Karma, Kourteye, and Namaro in 2024 and 2025.
The dataset can be used for flood rescue and recovery, an impact-based flood early warning system, local risk reduction planning, and local emergency planning.
DOI: 10.17632/9v349h653n.3
title: Flood risk assessment along the River Niger

description: The dataset used to build a novel Flood Risk Assessment (FRA) for semi-arid rural areas is provided here. Our FRA aims to address the recurring shortcomings in multi-hazard, participation, and risk reduction in the FRA for semi-arid rural regions published over the last decade.
We hypothesise that assessing flood risk by integrating high-resolution geoinformation and local knowledge in a participatory process enables the identification of risk reduction measures, thereby contributing to flood risk assessment in risk management.
Data show the flood-prone area of the River Niger upstream of the city of Niamey during local and Guinean floods, each with three probabilities of occurrence (return periods of 10, 30, and 100 years). Moreover, the data include the basin of the Karma Wadi (the largest tributary of the Niger River, which is reported to flood crops along the River Niger) and the highlands requiring treatment. Further information in the dataset includes assets exposed to each flood, expected damage, risk levels for each of the five municipalities along the river, potential risk-reduction measures, and their cost-benefit analyses.
The main findings of the FRA are: 
1) River flooding during the dry season causes more damage than during the wet season
2) Expected damage to irrigated crops is greater than damage to buildings
3) High-resolution geoinformation and local knowledge identify a feasible risk reduction
4) Raising the levees of rice fields, hygiene, and sanitation are priorities
5) High land prices hinder resettlement and redirect land development
The data consists of an Excel file reporting (i) crops, settlements, buildings (footprint and number) exposed to 6 flood scenarios organised by municipality; (ii) expected damage, (iii) SWOT analysis on measures; (iv) Measures priority; (v) Risk reduction; (vi) Cost-benefit analysis. Moreover, five folders contain shape files of flood-prone areas, categorised by six scenarios (two types of floods and three probabilities of occurrence each), water depth, and assets (crops and buildings). Finally, two figures in PNG format localise each flood-prone settlement mentioned in the tables.
Data were gathered from daily river discharge data provided by the Ministry of Hydraulics and Sanitation of Niger, a digital elevation model extracted from Planet satellite images and land cover Google Earth images of February 2024, the Information System on Rural Markets (SIMA), field inspections on February 2025, and focus groups conducted with the municipalities of Gothèye, Karma, Kourteye, and Namaro in 2024 and 2025.
The dataset can be used for flood rescue and recovery, an impact-based flood early warning system, local risk reduction planning, and local emergency planning.
DOI: 10.17632/r2mnkjfmh3
title: Multi-task synthetic dataset

description: A synthetic dataset collection designed for evaluating multi-task learning and transfer learning algorithms under both regression and binary classification settings. It consists of 100 independently generated batches, each initialized with distinct random seeds to promote diversity across tasks. Every batch contains 10 tasks (including two designated outliers), with 300 training and 1,000 test instances per task distributed across five input features. The dataset ensures balanced class representation and controlled task variation through a weighting parameter of w = 0.9.
DOI: 10.15468/dl.rsy3jv
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((115.481 -3.221832, 115.410626 -3.227396, 115.341983 -3.243952, 115.276758 -3.271093, 115.216556 -3.30815, 115.162858 -3.354214, 115.116986 -3.40815, 115.080069 -3.468632, 115.053018 -3.534171, 115.0365 -3.603155, 115.030924 -3.673886, 115.03643 -3.744623, 115.052884 -3.813623, 115.079886 -3.879187, 115.11677 -3.939699, 115.162631 -3.99367, 115.21634 -4.039768, 115.276575 -4.076857, 115.34185 -4.104022, 115.410556 -4.120594, 115.481 -4.126164, 115.551444 -4.120594, 115.62015 -4.104022, 115.685425 -4.076857, 115.74566 -4.039768, 115.799369 -3.99367, 115.84523 -3.939699, 115.882114 -3.879187, 115.909116 -3.813623, 115.92557 -3.744623, 115.931076 -3.673886, 115.9255 -3.603155, 115.908982 -3.534171, 115.881931 -3.468632, 115.845014 -3.40815, 115.799142 -3.354214, 115.745444 -3.30815, 115.685242 -3.271093, 115.620017 -3.243952, 115.551374 -3.227396, 115.481 -3.221832))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045233-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.