cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15350354
title: Novel Table Search (NTS) Datasets

description: Benchmark Datasets for Novel Table Search

This repository contains the datasets released alongside the paper “Novel Table Search.” We provide three benchmark datasets, each derived and adapted from existing benchmarks to suit the specific objectives of this work.

Contents

For each dataset, the following components are included:

• Ground Truth

Alignmnet ground truth files are provided:

• One manually curated column alignment (for Ugen-V2 Small)

• Two manually generated alignments based on column labels

Unionable Tables 

• Precomputed Embeddings

Vectors generated using the Starmie and TABBIE models are included to support reproducibility.

• Query and Data Lake Tables

All queries and associated data lake tables used in our experiments are provided.

• Processed Tables

Normalized table representations used in our experiments are included in the processed/ folder.
DOI: 10.5281/zenodo.15350355
title: Novel Table Search (NTS) Datasets

description: Benchmark Datasets for Novel Table Search

This repository contains the datasets released alongside the paper “Novel Table Search.” We provide three benchmark datasets, each derived and adapted from existing benchmarks to suit the specific objectives of this work.

Contents

For each dataset, the following components are included:

• Ground Truth

Alignmnet ground truth files are provided:

• One manually curated column alignment (for Ugen-V2 Small)

• Two manually generated alignments based on column labels

Unionable Tables 

• Precomputed Embeddings

Vectors generated using the Starmie and TABBIE models are included to support reproducibility.

• Query and Data Lake Tables

All queries and associated data lake tables used in our experiments are provided.

• Processed Tables

Normalized table representations used in our experiments are included in the processed/ folder.
DOI: 10.17026/dans-xgz-nts3
title: Plangebied Partycentrum de Zwerfkei te Gees, gemeente Coevorden

description: &lt;p&gt;onderzoeksrapport&lt;/p&gt;
DOI: 10.5281/zenodo.17819989
title: Data
DOI: 10.5281/zenodo.18377816
title: Data
DOI: 10.17909/rzn1-j577
title: From Paper: Baykara, Godon and Sion, A UV Spectroscopic Analysis of VY Scl during the deep low state of 1983. RNAAS 2026

description: This is the IUE dataset obtained when VY Scl was in a low state, and it is the lowest state observed with IUE.
DOI: 10.15468/dl.2rfsbc
title: Occurrence Download

description: A dataset containing 85579 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Impatiens capensis)",
 "OccurrenceStatus is Present",
 "SpeciesKey is not null",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2026",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 },
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation)"
 ]
}

 The dataset includes 85579 records from 146 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000041-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k3e6fv
title: Occurrence Download

description: A dataset listing the 36 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (SOM.17_1, SOM.1_1, SOM.13_1, SOM.16_1, SOM.18_1)",
 "OccurrenceStatus is Present",
 "TaxonKey is Arachnida"
 ]
}

 The dataset's 36 records were derived from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000059-260126135527185/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.31150477
title: Data S1

description: Zip file containing raw data and relevant sources, including: (<b>1</b>) Sources.xlsx – sources for skull reconstructions, as well as phylogenetic placements and age ranges of taxa not included in Singh et al.<sup>5</sup>, and node age constraints based on Matamales-Andreu et al.<sup>70</sup> (<b>2</b>) synapsidappended.tps – raw geometric morphometric landmark data. (<b>3</b>) synapsidslider.txt – slider file for sliding semilandmarks along curves. (<b>4</b>) functionalraw.xlsx – raw functional morphometric measurements and functional scores used for PCA and clustering analyses. (<b>5</b>) adjacency.xlsx – adjacency matrices used for anatomical network analysis. (<b>6</b>) imputedfunctiondata.csv – phylogenetically imputed functional data. (<b>7</b>) shapePC.csv – PC scores from 2D GM. (<b>8</b>) functionPC.csv – PC scores from PCA of imputed functional morphometric data. (<b>9</b>) FFGs.csv – FFG designations for all sampled taxa from consensus clustering results.
DOI: 10.6084/m9.figshare.31150477.v1
title: Data S1

description: Zip file containing raw data and relevant sources, including: (<b>1</b>) Sources.xlsx – sources for skull reconstructions, as well as phylogenetic placements and age ranges of taxa not included in Singh et al.<sup>5</sup>, and node age constraints based on Matamales-Andreu et al.<sup>70</sup> (<b>2</b>) synapsidappended.tps – raw geometric morphometric landmark data. (<b>3</b>) synapsidslider.txt – slider file for sliding semilandmarks along curves. (<b>4</b>) functionalraw.xlsx – raw functional morphometric measurements and functional scores used for PCA and clustering analyses. (<b>5</b>) adjacency.xlsx – adjacency matrices used for anatomical network analysis. (<b>6</b>) imputedfunctiondata.csv – phylogenetically imputed functional data. (<b>7</b>) shapePC.csv – PC scores from 2D GM. (<b>8</b>) functionPC.csv – PC scores from PCA of imputed functional morphometric data. (<b>9</b>) FFGs.csv – FFG designations for all sampled taxa from consensus clustering results.
DOI: 10.17632/sfxzbx4k8z
title: Dataset de Transferencia tecnológica en Macondo: Identificando los motivadores de los investigadores en los procesos de transferencia de tecnología en universidades colombianas

description: Data de la tesis doctoral de Simon Echeverry sobre Transferencia de Tecnología
DOI: 10.5683/sp3/mb9oon
title: Conditional emissivity prior for improved Bayesian pyrometry estimates of advanced high strength steel

description: This dataset contains the experimental measurements from annealing DP980, DP780 and IF steel samples, as well as the MATLAB code for obtained from predicting the steel temperature using a Bayesian Pyrometry model with a conditional emissivity prior. All the data collection and analysis procedures are detailed in the accompanying paper.
description: The paper has not been published yet, and the related publication section will be updated when the paper gets published.
description: MATLAB, R2022a
DOI: 10.17632/sfxzbx4k8z.2
title: Dataset de Transferencia tecnológica en Macondo: Identificando los motivadores de los investigadores en los procesos de transferencia de tecnología en universidades colombianas

description: Data de la tesis doctoral de Simon Echeverry sobre Transferencia de Tecnología
DOI: 10.17632/pykvcgs22y
title: Large-Scale Dataset of Porous Carbon Materials for Supercapacitors Extracted via Large Language Models

description: This dataset comprises a large-scale collection of experimental data on porous carbon supercapacitors, extracted from approximately 1,000 high-content research articles using an automated Large Language Model (LLM) mining framework.
The database covers over 5,000 distinct carbon samples and includes more than 10,000 specific capacitance data points under varying testing conditions. It offers a holistic view of the material properties, integrating synthesis parameters (preparation crafts), microstructural characteristics (pore size distribution, surface area), and surface elemental composition. Furthermore, it details key electrochemical performance metrics, including Specific Capacitance, Energy Density, Power Density, and Equivalent Series Resistance (ESR).
This dataset serves as a valuable resource for data-driven materials science, enabling quantitative analysis of structure-performance correlations and the inverse design of high-performance energy storage materials.
Note: For further modeling use, detailed data cleaning may be required for specific domains

The ml_use_data folder contains two datasets: the number_metric_dataset_cleaned.csv (9,962 entries), which serves as the cleaned feature pool, and the train_test_dataset.csv (284 entries), a subset derived by filtering out non-null features for model training and testing.
DOI: 10.17632/pykvcgs22y.2
title: Large-Scale Dataset of Porous Carbon Materials for Supercapacitors Extracted via Large Language Models

description: This dataset comprises a large-scale collection of experimental data on porous carbon supercapacitors, extracted from approximately 1,000 high-content research articles using an automated Large Language Model (LLM) mining framework.
The database covers over 5,000 distinct carbon samples and includes more than 10,000 specific capacitance data points under varying testing conditions. It offers a holistic view of the material properties, integrating synthesis parameters (preparation crafts), microstructural characteristics (pore size distribution, surface area), and surface elemental composition. Furthermore, it details key electrochemical performance metrics, including Specific Capacitance, Energy Density, Power Density, and Equivalent Series Resistance (ESR).
This dataset serves as a valuable resource for data-driven materials science, enabling quantitative analysis of structure-performance correlations and the inverse design of high-performance energy storage materials.
Note: For further modeling use, detailed data cleaning may be required for specific domains

The ml_use_data folder contains two datasets: the number_metric_dataset_cleaned.csv (9,962 entries), which serves as the cleaned feature pool, and the train_test_dataset.csv (284 entries), a subset derived by filtering out non-null features for model training and testing.
DOI: 10.17632/hr5h2hcgg4
title: Chorological data for the main European woody species

description: The data are organized as a set of ESRI shapefiles (*.shp, *.shx, *.dbf, *.prj files) mapping the distribution ranges of the main European tree and shrub species. For each species and in some cases subspecies, one or more shapefiles have been created containing: a) polygon features (name suffix “plg”), which define continuous areas of occupancy of the species range and b) point features (name suffix “pnt”), which identify more fragmented and isolated populations. For species with reported synanthropic occurrences outside the natural range, an additional point and/or polygon shapefile has also been created (suffix “syn”). Polygon borders delimiting species ranges are generalized across the mainland and sea boundaries. This offers the possibility to mask sea areas or to clip and extract the terrestrial range parts using GIS data layers of the users' choice. An additional version of polygon ranges are clipped with a coastline (name suffix “clip”), which have been derived from Natural Earth dataset "Admin 0 - Countries" 1:50M version 4.1.0 (https://www.naturalearthdata.com). Finally, an accompanying text document is included with the data, which provides more details on methodology and a list of all mapped species with related file names, taxonomical delimitation of the mapped species and references used to compile the respective chorological dataset.
DOI: 10.17632/hr5h2hcgg4.19
title: Chorological data for the main European woody species

description: The data are organized as a set of ESRI shapefiles (*.shp, *.shx, *.dbf, *.prj files) mapping the distribution ranges of the main European tree and shrub species. For each species and in some cases subspecies, one or more shapefiles have been created containing: a) polygon features (name suffix “plg”), which define continuous areas of occupancy of the species range and b) point features (name suffix “pnt”), which identify more fragmented and isolated populations. For species with reported synanthropic occurrences outside the natural range, an additional point and/or polygon shapefile has also been created (suffix “syn”). Polygon borders delimiting species ranges are generalized across the mainland and sea boundaries. This offers the possibility to mask sea areas or to clip and extract the terrestrial range parts using GIS data layers of the users' choice. An additional version of polygon ranges are clipped with a coastline (name suffix “clip”), which have been derived from Natural Earth dataset "Admin 0 - Countries" 1:50M version 4.1.0 (https://www.naturalearthdata.com). Finally, an accompanying text document is included with the data, which provides more details on methodology and a list of all mapped species with related file names, taxonomical delimitation of the mapped species and references used to compile the respective chorological dataset.
DOI: 10.5281/zenodo.18305751
title: TFBindFormer_dataset

description: This dataset contains the training, validation, and test data used for transcription factor (TF)–DNA binding prediction in the TFBindFormer framework. It integrates genomic DNA sequence bins with transcription factor protein information, including amino-acid sequences and structure-derived 3Di representations. The dataset is organized into clearly separated DNA and TF components to facilitate reproducible model training and evaluation.
DOI: 10.5281/zenodo.18305750
title: TFBindFormer_dataset

description: This dataset contains the training, validation, and test data used for transcription factor (TF)–DNA binding prediction in the TFBindFormer framework. It integrates genomic DNA sequence bins with transcription factor protein information, including amino-acid sequences and structure-derived 3Di representations. The dataset is organized into clearly separated DNA and TF components to facilitate reproducible model training and evaluation.
DOI: 10.17632/x9kpkg2ktk
title: Code and derived datasets for reanalysis uncertainty in daily Tmax and Tmin over the Tibetan Plateau (1980–2018)

description: This repository contains analysis code and derived, non-restricted outputs supporting the figures and conclusions of the manuscript, including station-wise evaluation metrics, trend estimates, and temperature-extreme and frost-threshold indices. CMA station daily Tmax/Tmin observations are third-party restricted and are not redistributed; reanalysis inputs are publicly available from their official providers.
DOI: 10.17632/x9kpkg2ktk.1
title: Code and derived datasets for reanalysis uncertainty in daily Tmax and Tmin over the Tibetan Plateau (1980–2018)

description: This repository contains analysis code and derived, non-restricted outputs supporting the figures and conclusions of the manuscript, including station-wise evaluation metrics, trend estimates, and temperature-extreme and frost-threshold indices. CMA station daily Tmax/Tmin observations are third-party restricted and are not redistributed; reanalysis inputs are publicly available from their official providers.
DOI: 10.6084/m9.figshare.31150421
title: Explainable GeoAI reveals spatially varying and nonlinear associations of PM<sub>2.5</sub> pollution with driving factors in Chinese cities from 2015 to 2022

description: PM<sub>2.5</sub> pollution remains a critical environmental and public health challenge in China despite post-2015 improvements. However, our understanding of the spatially heterogeneous and nonlinear associations of its driving factors remains limited. To fill this gap, we employ an explainable geospatial artificial intelligence (GeoAI) framework that integrates the geographical random forest (GRF) model and the Shapley additive explanations (SHAP) approach to examine the associations between 16 determinants and PM<sub>2.5</sub> concentrations. Based on a nationwide and multi-year analysis across 288 cities selected from all 336 Chinese cities between 2015 and 2022, the results show that GRF achieves at least a 0.04 higher R² than baseline models. Our analysis reveals three findings. First, population density is the most influential factor in 52.39% of cities; combined with temperature, road density, and gas supply, these four dominate over 95% of cities. Second, drivers exhibit significant spatially varying and nonlinear associations. For instance, population density correlates positively with PM<sub>2.5</sub> in the North China Plain but negatively in sparsely populated areas; and the association of temperature follows an inverted U-shaped pattern. Third, these spatial and nonlinear associations undergo temporal changes. These findings offer insights for future environmental management strategies to mitigate the negative impacts of various drivers.
DOI: 10.6084/m9.figshare.31150421.v1
title: Explainable GeoAI reveals spatially varying and nonlinear associations of PM<sub>2.5</sub> pollution with driving factors in Chinese cities from 2015 to 2022

description: PM<sub>2.5</sub> pollution remains a critical environmental and public health challenge in China despite post-2015 improvements. However, our understanding of the spatially heterogeneous and nonlinear associations of its driving factors remains limited. To fill this gap, we employ an explainable geospatial artificial intelligence (GeoAI) framework that integrates the geographical random forest (GRF) model and the Shapley additive explanations (SHAP) approach to examine the associations between 16 determinants and PM<sub>2.5</sub> concentrations. Based on a nationwide and multi-year analysis across 288 cities selected from all 336 Chinese cities between 2015 and 2022, the results show that GRF achieves at least a 0.04 higher R² than baseline models. Our analysis reveals three findings. First, population density is the most influential factor in 52.39% of cities; combined with temperature, road density, and gas supply, these four dominate over 95% of cities. Second, drivers exhibit significant spatially varying and nonlinear associations. For instance, population density correlates positively with PM<sub>2.5</sub> in the North China Plain but negatively in sparsely populated areas; and the association of temperature follows an inverted U-shaped pattern. Third, these spatial and nonlinear associations undergo temporal changes. These findings offer insights for future environmental management strategies to mitigate the negative impacts of various drivers.
DOI: 10.15468/dd.9s6g6j
title: Dataset generated from Esri tool

description: Derived dataset generated by Esri geoprocessing tool using GBIF API
DOI: 10.5281/zenodo.18001007
title: FEMVitisDataset

description: The FEMVitisDataset provides curated genotypic, taxonomic and phenotypic data for 2,904 grapevine accessions conserved at the Edmund Mach Foundation in San Michele all’Adige, Italy (46°11’N, 11°08’E, 223 m asl, FAO holding institution ITA362). The dataset is organised into six Excel (xlsx) files, each corresponding to a distinct data domain. Together, these files provide an interoperable and FAIR-compliant resource supporting grapevine germplasm management, cultivar identification, and integrative analyses of genotypic and phenotypic diversity.
DOI: 10.5281/zenodo.18001008
title: FEMVitisDataset

description: The FEMVitisDataset provides curated genotypic, taxonomic and phenotypic data for 2,904 grapevine accessions conserved at the Edmund Mach Foundation in San Michele all’Adige, Italy (46°11’N, 11°08’E, 223 m asl, FAO holding institution ITA362). The dataset is organised into six Excel (xlsx) files, each corresponding to a distinct data domain. Together, these files provide an interoperable and FAIR-compliant resource supporting grapevine germplasm management, cultivar identification, and integrative analyses of genotypic and phenotypic diversity.
DOI: 10.15468/dl.f748hb
title: Occurrence Download

description: A dataset containing 36515 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Taxon occurrence data for the FungalRoot database"
 ]
}

 The dataset includes 36515 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000085-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14627893
title: Mahanagar Yatayat Transport Dataset
DOI: 10.5281/zenodo.18377969
title: ML-derived CCN from HSRL-2 during the NASA ACTIVATE campaign

description: ML-derived CCN concentration at 0.4% supersaturation from HSRL-2 during the NASA ACTIVATE campaign.
DOI: 10.5281/zenodo.18377970
title: ML-derived CCN from HSRL-2 during the NASA ACTIVATE campaign

description: ML-derived CCN concentration at 0.4% supersaturation from HSRL-2 during the NASA ACTIVATE campaign.
DOI: 10.25574/28675
title: Chandra X-ray Observatory ObsId 28675

description: Chandra Observations of a Star-Bursting Cluster of Galaxies at z=1.034
DOI: 10.6084/m9.figshare.31150492
title: Data S2

description: Zip file containing phylogenetic data, including: (<b>1</b>) synapsidnewick.tre – Newick-formatted phylogenetic tree with no edge lengths (i.e., non-time scaled phylogeny). (<b>2</b>) synapsidages.csv – taxon age ranges used for time tree generation. (<b>3</b>) synapsidtree.rds – complete time tree, as R file.
DOI: 10.6084/m9.figshare.31150492.v1
title: Data S2

description: Zip file containing phylogenetic data, including: (<b>1</b>) synapsidnewick.tre – Newick-formatted phylogenetic tree with no edge lengths (i.e., non-time scaled phylogeny). (<b>2</b>) synapsidages.csv – taxon age ranges used for time tree generation. (<b>3</b>) synapsidtree.rds – complete time tree, as R file.
DOI: 10.5281/zenodo.18378010
title: LINF_320009100

description: ATP-dependent RNA helicase HEL67 | DED1-1 | DBP1 | DDX3; Leishmania infantum (strain JPCM5)
DOI: 10.5281/zenodo.18378009
title: LINF_320009100

description: ATP-dependent RNA helicase HEL67 | DED1-1 | DBP1 | DDX3; Leishmania infantum (strain JPCM5)
DOI: 10.15468/dl.rtaa7f
title: Occurrence Download

description: A dataset containing 1441690 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Croatia"
 ]
}

 The dataset includes 1441690 records from 1313 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000001-260126113818162/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dd.kz96b5
title: Dataset generated from Esri tool

description: Derived dataset generated by Esri geoprocessing tool using GBIF API
DOI: 10.5281/zenodo.18377817
title: Global fragmentation trends during 2000-2020

description: Updated data (corrected for a small number of missing pixels in the US and Africa) to reproduce the analysis in the paper "Forest fragmentation increased in over half of global forests from 2000 to 2020". It is impossible to include all of the source data in this dataset, which is too large (more than 800 GB). The 30m resolution tree cover data for the years 2000 and 2020 were downloaded from "https://glad.umd.edu/users/Potapov/GLCLUC2020/Forest_extent_2000/" and "https://glad.umd.edu/users/Potapov/GLCLUC2020/Forest_extent_2020/".
DOI: 10.5281/zenodo.14883208
title: Global fragmentation trends during 2000-2020

description: Updated data (corrected for a small number of missing pixels in the US and Africa) to reproduce the analysis in the paper "Forest fragmentation increased in over half of global forests from 2000 to 2020". It is impossible to include all of the source data in this dataset, which is too large (more than 800 GB). The 30m resolution tree cover data for the years 2000 and 2020 were downloaded from "https://glad.umd.edu/users/Potapov/GLCLUC2020/Forest_extent_2000/" and "https://glad.umd.edu/users/Potapov/GLCLUC2020/Forest_extent_2020/".