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

description: A dataset containing 1016 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Italy",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Taxus baccata L."
 ]
}

 The dataset includes 1016 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007171-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vpuvub
title: Occurrence Download

description: A dataset containing 643297 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 643297 records from 128 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007139-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9j7799
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-9.76618 35.85612,-6.50666 35.85612,-6.50666 42.46527,-9.76618 42.46527,-9.76618 35.85612))",
 "TaxonKey is Halopeplis amplexicaulis (Vahl) Ung.-Sternb. ex Ces., Pass. & Gibelli",
 "Year 1975-2025"
 ]
}

 The dataset includes 17 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007172-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2pn8vt
title: Occurrence Download

description: A dataset listing the 134 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-78.8941 -1.16441,-78.87792 -1.25159,-78.76684 -1.23858,-78.75383 -1.17952,-78.81043 -1.16072,-78.8941 -1.16441))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 134 records were derived from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007155-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5mb38b
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "TaxonKey is Scleranthus perennis L.",
 "Year 1975-2025"
 ]
}

 The dataset includes 13 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007173-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zr7zx4
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Venezuela (Bolivarian Republic of)",
 "TaxonKey is Atya scabra (Leach, 1816)"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007174-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gfvp83
title: Occurrence Download

description: A dataset containing 205208 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Fallopia japonica (Houtt.) Ronse Decr."
 ]
}

 The dataset includes 205208 records from 517 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007151-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7dmsvj
title: Occurrence Download

description: A dataset containing 580 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Prunus pseudocerasus Lindl."
 ]
}

 The dataset includes 580 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007175-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29086454
title: VS-FPM: large-format, label-free virtual histopathology microscopy

description: <b>Abstract</b>By generating realistic histologically stained images from label-free image data, virtual staining (VS) methods have the potential to streamline clinical workflows, improve image consistency and enable new ways of visualizing and analysing tissues. This article describes a new VS approach based on the application of conditional generative adversarial networks to translate high-resolution phase images of unstained tissues, recovered using Fourier ptychographic microscopy (FPM), into brightfield H&E images. Compared to other label-free imaging methods, FPM offers unique advantages for VS as it allows simultaneous capture of sample amplitude and phase information, simplifying the pixelwise registration required for supervised training. FPM combines high spatial resolution with a large field of view and a large depth of field making it well suited to large format imaging of histological tissues. The method is readily implemented by modifying a conventional brightfield microscope using simple, low-cost optoelectronic hardware. Using colonic polyps as a test case, we compare FPM and VS-FPM images to brightfield whole slide images (WSIs) captured using a pathology slide scanner. Our results show that FPM images captured at 4x magnification have a spatial resolution equivalent to WSIs captured at 20x magnification and virtual H&E images of unstained tissues generated using VS-FPM closely match brightfield images of the same tissue sections captured after chemical staining, enabling pathological assessment and diagnosis.<b>Dataset:</b>This dataset contains pathology images of intestinal polyps from 3 patients. For each polyp section, there is are 4 registered images, 3 of which are chemically stained with H&E: WSI (captured with a NanoZoomer S360MD), FPM reconstructed amplitude and raw 4x brightfield. The 4th image is virtually stained from FPM phase images of unstained tissue.<br>
DOI: 10.23729/fd-a5f525c6-41ce-3b0b-bfc7-7021dd641c1d
title: Termite mounds studied in Taita-Taveta, Kenya

description: Data set includes geographical coordinates (WGS84, decimal degrees) and basic information (mound type, termite species, identities of the symbiotic Termitomyces fungi, external dimensions) about the termite mounds studied in Taita Taveta area (Kenya) in various studies and research projects including 'IsoTermes' project funded by Research Council of Finland (2020-2024). Data set consists of both active termite mounds built and maintained by termite species Macrotermes michaelseni and Macrotermes subhyalinus and ancient (inactive) termite hills sampled for paleoecological research including dating analysis.
DOI: 10.15468/dl.gvscra
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-9.34552 36.08812,-6.61244 36.08812,-6.61244 42.20817,-9.34552 42.20817,-9.34552 36.08812))",
 "HasCoordinate is true",
 "TaxonKey is Helianthemum cinereum (Cav.) Pers.",
 "Year 1975-2025"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007178-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yyduct
title: Occurrence Download

description: A dataset containing 261 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 Myoschilos Ruiz & Pav."
 ]
}

 The dataset includes 261 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007177-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29099186
title: test.txt

description: test
DOI: 10.6084/m9.figshare.29099186.v1
title: test.txt

description: test
DOI: 10.5281/zenodo.12690506
title: Exome-wide association analysis (ExWAS) of clonal haematopoiesis in 136,401 Admixed Americans and 416,118 Europeans

description: We performed exome-wide association analysis (ExWAS) of germline genetic variants identified from whole-exome sequencing (WES) to identify novel inherited genetic determinants of clonal haematopoiesis (CH). Here, we provide the summary statistics from ExWAS CH performed on Admixed Americans recruited to the Mexico City Prospective Study (MCPS), Europeans recruited to the United Kingdom Biobank (UKB), and cross-ancestry meta-analysis of Admixed Americans and Europeans. Analyses was performed with REGENIE software (Firth's logistic regression), Fisher's exact test, and METAL software (inverse variance-weighted average method to derive effect size and P-value method to derive P value), respectively.

 

In version 1 of this repository, UKB variants (*_UKB.tsv) with minor allele frequency (MAF) 1% or more were uploaded. In version 2, this is now rectified so that rare variants with MAF of 0.1% or more were uploaded. This threshold now matches the MCPS (*_MCPS.tsv) and UKB-MCPS meta-analysis summary statistics (*_MCPS-UKB_meta-analysis.tsv)
DOI: 10.5281/zenodo.15464179
title: Exome-wide association analysis (ExWAS) of clonal haematopoiesis in 136,401 Admixed Americans and 416,118 Europeans

description: We performed exome-wide association analysis (ExWAS) of germline genetic variants identified from whole-exome sequencing (WES) to identify novel inherited genetic determinants of clonal haematopoiesis (CH). Here, we provide the summary statistics from ExWAS CH performed on Admixed Americans recruited to the Mexico City Prospective Study (MCPS), Europeans recruited to the United Kingdom Biobank (UKB), and cross-ancestry meta-analysis of Admixed Americans and Europeans. Analyses was performed with REGENIE software (Firth's logistic regression), Fisher's exact test, and METAL software (inverse variance-weighted average method to derive effect size and P-value method to derive P value), respectively.

 

In version 1 of this repository, UKB variants (*_UKB.tsv) with minor allele frequency (MAF) 1% or more were uploaded. In version 2, this is now rectified so that rare variants with MAF of 0.1% or more were uploaded. This threshold now matches the MCPS (*_MCPS.tsv) and UKB-MCPS meta-analysis summary statistics (*_MCPS-UKB_meta-analysis.tsv)
DOI: 10.15468/dl.8raegx
title: Occurrence Download

description: A dataset containing 140 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Romania",
 "OccurrenceStatus is Present",
 "TaxonKey is Lutra Brisson, 1762"
 ]
}

 The dataset includes 140 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007179-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vmr7x4
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-10.06295 36.76427,-5.87556 36.76427,-5.87556 41.98827,-10.06295 41.98827,-10.06295 36.76427))",
 "TaxonKey is Herniaria lusitanica subsp. berlengiana Chaudhri",
 "Year 1975-2025"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007180-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.45pj3h
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Occurrence evidence",
 "Country is Romania",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Lutra Brisson, 1762, Hydropsyche instabilis (Curtis, 1834))",
 "Year 2007-2025"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007181-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15464163
title: Simulation input scripts for "High brightness, symmetric electron bunch generation in a plasma wakefield accelerator via a radially-polarized plasma photocathode"

description: This dataset presents the input scripts required to re-create the data of the figures in the article "High brightness, symmetric electron bunch generation in a plasma wakefield accelerator via a radially-polarized plasma photocathode".
DOI: 10.5281/zenodo.15464164
title: Simulation input scripts for "High brightness, symmetric electron bunch generation in a plasma wakefield accelerator via a radially-polarized plasma photocathode"

description: This dataset presents the input scripts required to re-create the data of the figures in the article "High brightness, symmetric electron bunch generation in a plasma wakefield accelerator via a radially-polarized plasma photocathode".
DOI: 10.5281/zenodo.15436304
title: Supplementary Material | Energy Modelling Research Landscape in Kenya: A Systematic Review.

description: This dataset presents the data used to conduct the analysis in the literature review titled 'Energy Modelling Research Landscape in Kenya: A Systematic Review'.

This material has been produced under the Climate Compatible Growth (CCG) programme, which brings together leading research organisations and is led out of the STEER centre, Loughborough University. CCG is funded by UK aid from the UK government. However, the views expressed herein do not necessarily reflect the UK government's official policies
DOI: 10.5281/zenodo.15436305
title: Supplementary Material | Energy Modelling Research Landscape in Kenya: A Systematic Review.

description: This dataset presents the data used to conduct the analysis in the literature review titled 'Energy Modelling Research Landscape in Kenya: A Systematic Review'.

This material has been produced under the Climate Compatible Growth (CCG) programme, which brings together leading research organisations and is led out of the STEER centre, Loughborough University. CCG is funded by UK aid from the UK government. However, the views expressed herein do not necessarily reflect the UK government's official policies
DOI: 10.60797/irj.2025.155.104.8
title: Коэффициент сходства (Жаккара) видовых списков насаждений изученных прихрамовых территорий

description: Международный научно-исследовательский журнал, Выпуск 5 (155) 2025
DOI: 10.7910/dvn/cc8z9a
title: Designing Effective Heat Adaptation Portfolios: Evidence from Policy Interactions and Mortality Risk in South Korea

description: This dataset contains regional (si-gun-gu) level panel data for the research title of "Designing Effective Heat Adaptation Portfolios: Evidence from Policy Interactions and Mortality Risk in South Korea". 

The dataset includes: `panel_heatwave_dataverse.xlsx`: - The dataset comprises raw, regional-level data collected from various sources including Statistics Korea and Korea Meteorological Administration. The descriptions of the variables are provided in English.
description: This dataset contains regional (si-gun-gu) level panel data used in the study titled “Designing Effective Heat Adaptation Portfolios: Evidence from Policy Interactions and Mortality Risk in South Korea.”

The file panel_heatwave_dataverse.xlsx includes raw panel data at the regional level, compiled from various sources such as Statistics Korea and the Korea Meteorological Administration. Variable descriptions are provided in English.
DOI: 10.7910/dvn/zsqfsj
title: x-sa-crop-type

description: This dataset was developed as part of the Radiant Earth "Spot the Crop" Challenge. It includes 5,000 paired multispectral (MS) and synthetic aperture radar (SAR) image patches. While the MS and SAR images are temporally close, they may have been acquired on slightly different dates. For each pair, the SAR image was selected to be the closest available in time to the corresponding MS image. (2025-05-10)
DOI: 10.5281/zenodo.6613714
title: LNDb Dataset

description: The Lung Nodule Database (LNDb) was developed as an external dataset complimentary to LIDCIDRI. The publication of this database gives continuity to LIDC-IDRI and allows the community to perform an external and comparable validation of proposed computer-aided diagnosis (CAD) systems. The LNDb contains 294 CT scans collected retrospectively at the Centro Hospitalar e Universitário de São João (CHUSJ) in Porto, Portugal between 2016 and 2018. All data was acquired under approval from the CHUSJ Ethical Commitee and was anonymised prior to any analysis to remove personal information except for patient birth year and gender. The database served as the basis for the Grand Challenge on automatic lung cancer patient management, or LNDb challenge. THIS DATASET IS PUBLICALLY AVAILABLE UNDER A CREATIVE COMMONS CC BY-NC-ND LICENSE (ATTRIBUTION-NONCOMMERCIAL-NODERIVS)<br> ESSENCIALLY, YOU ARE GRANTED ACCESS TO THE DATASET FOR USE IN YOUR RESEARCH AS LONG AS YOU CREDIT OUR WORK/PUBLICATIONS(*), BUT YOU CANNOT CHANGE THEM IN ANY WAY OR USE THEM COMMERCIALLY (*) Pedrosa, João, et al. "LNDb: a lung nodule database on computed tomography." <em>arXiv preprint arXiv:1911.08434</em> (2019). (*) Pedrosa, João, et al. "LNDb challenge on automatic lung cancer patient management." <em>Medical image analysis</em> 70 (2021): 102027.
description: This work was financed by the European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness - COMPETE 2020 Programme and by National Funds through the Portuguese Funding agency, FCT Fundaçãoo para a Ciência e Tecnologia within project PTDC/EEI-SII/6599/2014 (POCI01-0145-FEDER-016673).
description: {"references": ["Pedrosa, Jo\u00e3o, et al. \"LNDb: a lung nodule database on computed tomography.\"\u00a0arXiv preprint arXiv:1911.08434\u00a0(2019).", "Pedrosa, Jo\u00e3o, et al. \"LNDb challenge on automatic lung cancer patient management.\"\u00a0Medical image analysis\u00a070 (2021): 102027."]}
DOI: 10.5281/zenodo.7153205
title: LNDb Dataset

description: The Lung Nodule Database (LNDb) was developed as an external dataset complimentary to LIDCIDRI. The publication of this database gives continuity to LIDC-IDRI and allows the community to perform an external and comparable validation of proposed computer-aided diagnosis (CAD) systems. The LNDb contains 294 CT scans collected retrospectively at the Centro Hospitalar e Universitário de São João (CHUSJ) in Porto, Portugal between 2016 and 2018. All data was acquired under approval from the CHUSJ Ethical Commitee and was anonymised prior to any analysis to remove personal information except for patient birth year and gender. The database served as the basis for the Grand Challenge on automatic lung cancer patient management, or LNDb challenge. THIS DATASET IS PUBLICALLY AVAILABLE UNDER A CREATIVE COMMONS CC BY-NC-ND LICENSE (ATTRIBUTION-NONCOMMERCIAL-NODERIVS)<br> ESSENCIALLY, YOU ARE GRANTED ACCESS TO THE DATASET FOR USE IN YOUR RESEARCH AS LONG AS YOU CREDIT OUR WORK/PUBLICATIONS(*), BUT YOU CANNOT CHANGE THEM IN ANY WAY OR USE THEM COMMERCIALLY (*) Pedrosa, João, et al. "LNDb: a lung nodule database on computed tomography." <em>arXiv preprint arXiv:1911.08434</em> (2019). (*) Pedrosa, João, et al. "LNDb challenge on automatic lung cancer patient management." <em>Medical image analysis</em> 70 (2021): 102027.
description: This work was financed by the European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness - COMPETE 2020 Programme and by National Funds through the Portuguese Funding agency, FCT Fundaçãoo para a Ciência e Tecnologia within project PTDC/EEI-SII/6599/2014 (POCI01-0145-FEDER-016673).
description: {"references": ["Pedrosa, Jo\u00e3o, et al. \"LNDb: a lung nodule database on computed tomography.\"\u00a0arXiv preprint arXiv:1911.08434\u00a0(2019).", "Pedrosa, Jo\u00e3o, et al. \"LNDb challenge on automatic lung cancer patient management.\"\u00a0Medical image analysis\u00a070 (2021): 102027."]}
DOI: 10.5281/zenodo.8309612
title: LNDb Dataset

description: The Lung Nodule Database (LNDb) was developed as an external dataset complimentary to LIDCIDRI. The publication of this database gives continuity to LIDC-IDRI and allows the community to perform an external and comparable validation of proposed computer-aided diagnosis (CAD) systems.


The LNDb contains 294 CT scans collected retrospectively at the Centro Hospitalar e Universitário de São João (CHUSJ) in Porto, Portugal between 2016 and 2018. All data was acquired under approval from the CHUSJ Ethical Commitee and was anonymised prior to any analysis to remove personal information except for patient birth year and gender.


The database served as the basis for the Grand Challenge on automatic lung cancer patient management, or LNDb challenge.


THIS DATASET IS PUBLICALLY AVAILABLE UNDER A CREATIVE COMMONS CC BY-NC-ND LICENSE (ATTRIBUTION)
ESSENCIALLY, YOU ARE GRANTED ACCESS TO THE DATASET FOR USE IN YOUR RESEARCH AS LONG AS YOU CREDIT OUR WORK/PUBLICATIONS(*)



	
(*) Pedrosa, João, et al. "LNDb: a lung nodule database on computed tomography." arXiv preprint arXiv:1911.08434 (2019).
	
(*) Pedrosa, João, et al. "LNDb challenge on automatic lung cancer patient management." Medical image analysis 70 (2021): 102027.
description: This work was financed by the European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness - COMPETE 2020 Programme and by National Funds through the Portuguese Funding agency, FCT Fundaçãoo para a Ciência e Tecnologia within project PTDC/EEI-SII/6599/2014 (POCI01-0145-FEDER-016673).
DOI: 10.7910/dvn/f2usny
title: x-so2sat
title: So2Sat

description: So2Sat is a multimodal dataset developed for urban land use and land cover classification. This subset, m-So2Sat, contains 22,000 paired Sentinel-1 (SAR) and Sentinel-2 (multispectral) image patches, each of size 32×32 pixels. The data is annotated with 17 urban land use and land cover classes, enabling robust benchmarking for multimodal and multi-class classification tasks.
&lt;br&gt;
In this version, the only modification applied to the original dataset is a preprocessing step to transform the Sentinel-1 VV and VH bands into their absolute values, enhancing interpretability and consistency across samples. The original pairing of Sentinel-1 and Sentinel-2 data is preserved.
DOI: 10.15468/dl.hhp6ab
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Occurrence evidence",
 "Country is Romania",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Lutra Brisson, 1762, Hydropsyche instabilis (Curtis, 1834))",
 "Year 2007-2025"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007183-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34973/2mye-8468
title: MythFic Metadata: Exploring Gendered Violence in Fanfiction about Greek Mythology

description: Metadata and Analysis Spreadsheets for the DH Benelux 2023 paper