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

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nemotaulius mutatus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 16 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000632-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.42g44x
title: Occurrence Download

description: A dataset containing 7 records in GBIF matching the query:
SELECT
 genus,
 species,
 COUNT(*) total_registros
FROM
 occurrence
WHERE
 occurrence.countrycode = 'CL'
 AND occurrence.genus IN ('Sephanoides', 'Pteroptochos', 'Scytalopus')
 AND occurrence."month" IN (10, 11)
 AND occurrence.species IS NOT NULL
GROUP BY
 occurrence.genus,
 occurrence.species
ORDER BY
 total_registros DESC

 The dataset's 7 records were derived from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000627-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wej22y
title: Occurrence Download

description: A dataset containing 7 records in GBIF matching the query:
SELECT
 genus,
 species,
 COUNT(*) total_registros
FROM
 occurrence
WHERE
 occurrence.countrycode = 'CL'
 AND occurrence.genus IN ('Sephanoides', 'Pteroptochos', 'Scytalopus')
 AND occurrence."month" IN (10, 11)
 AND occurrence.species IS NOT NULL
GROUP BY
 occurrence.genus,
 occurrence.species
ORDER BY
 total_registros DESC

 The dataset's 7 records were derived from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000629-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.djne9r
title: Occurrence Download

description: A dataset containing 82 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hydatophylax soldatovi",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 82 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000635-260120142942310/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.26424253
title: Global habitat hotspots and extinction vulnerability of terrestrial vertebrates

description: Protecting critical habitats globally is essential to buffer threatened species from extinction due to anthropogenic stressors. However, limited understanding of the global distribution patterns of habitats for threatened terrestrial vertebrates and their associated habitat hotspots hinders efforts aimed at assessing biodiversity vulnerability and developing targeted conservation strategies. In this study, we integrated spatial data from the IUCN Red List with a deep learning approach to evaluate habitat distribution for 4,851 threatened species and construct a global niche interaction network. These habitat hotspots cover only 4% of the terrestrial surface but encompass 67.9% of all analyzed species. While vast unoccupied habitats exist, 76.8% of them remain geographically isolated by continental or oceanic barriers and are significantly affected by human pressures. Species at higher risk of extinction often have a larger proportion of unoccupied habitats, but geographic isolation limits these ecological opportunities. We identified regions where unoccupied habitats are concentrated and have long-term persistence potential. Furthermore, the continued loss of native habitats for species inhabiting islands or continental margins due to human pressures may accelerate the widespread homogenization of global niches, underscoring the rarity and irreplaceability of these fragile habitats. Our global assessment provides useful perspectives on sustainable conservation planning.
DOI: 10.6084/m9.figshare.26424253.v1
title: Global habitat hotspots and extinction vulnerability of terrestrial vertebrates

description: Protecting critical habitats globally is essential to buffer threatened species from extinction due to anthropogenic stressors. However, limited understanding of the global distribution patterns of habitats for threatened terrestrial vertebrates and their associated habitat hotspots hinders efforts aimed at assessing biodiversity vulnerability and developing targeted conservation strategies. In this study, we integrated spatial data from the IUCN Red List with a deep learning approach to evaluate habitat distribution for 4,851 threatened species and construct a global niche interaction network. These habitat hotspots cover only 4% of the terrestrial surface but encompass 67.9% of all analyzed species. While vast unoccupied habitats exist, 76.8% of them remain geographically isolated by continental or oceanic barriers and are significantly affected by human pressures. Species at higher risk of extinction often have a larger proportion of unoccupied habitats, but geographic isolation limits these ecological opportunities. We identified regions where unoccupied habitats are concentrated and have long-term persistence potential. Furthermore, the continued loss of native habitats for species inhabiting islands or continental margins due to human pressures may accelerate the widespread homogenization of global niches, underscoring the rarity and irreplaceability of these fragile habitats. Our global assessment provides useful perspectives on sustainable conservation planning.
DOI: 10.18170/dvn/evoabb
title: Index of Industrial Clusters in China

description: 1. The detailed calculation process of the index, please refer to our paper published in CER “A Measure of Industrial Clustering: Considering Relatedness and Scale” 2. We multiply the clustering index by 100 for scaling purposes in our paper “A Measure of Industrial Clustering: Considering Relatedness and Scale”. If you use this index in your research, we advise multiplying it by 100 too.
DOI: 10.34740/kaggle/dsv/13812903
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.u9y9kq
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Annellophragmia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001765-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gee8r2
title: Occurrence Download

description: A dataset containing 2303 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chaetosphaeronema",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2303 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001766-251120083545085/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.30673571.v2
title: Federal University of Health Sciences, Otukpo, Benue State 2025/2026 admission list (2nd and 3rd) are out call???? 08053738196. Mr Ben 08053738196. for help into the 3rd And final Batch call Registrar 08053738196. processing of admission into any department and purchasing of 2025/2026 last supplementary form for new student into any program call the school admission office now on 08053738196.

description: Federal University of Health Sciences, Otukpo, Benue State 2025/2026 admission list (2nd and 3rd) are out call📞 08053738196. Mr Ben 08053738196. for help into the 3rd And final Batch call Registrar 08053738196. processing of admission into any department and purchasing of 2025/2026 last supplementary form for new student into any program call the school admission office now on 08053738196.
DOI: 10.15468/dl.ssps8u
title: Occurrence Download

description: A dataset containing 12011 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Papilionidae)",
 "Country is one of (China)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12011 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001767-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bk5u9n
title: Occurrence Download

description: A dataset containing 10209 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pheidole megacephala"
 ]
}

 The dataset includes 10209 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001768-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.smmjw3
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Crucellisporiopsis",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001769-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6qd88m
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hapalosphaeria",
 "HasCoordinate is true"
 ]
}

 The dataset includes 45 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001770-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17667854
title: GENERATOR DATASET SLIK OJK

description: DATASET PERMINTAAN SLIK OJK ASURANSI KREDIT DAN SURETYSHIP
DOI: 10.5281/zenodo.17667855
title: GENERATOR DATASET SLIK OJK

description: DATASET PERMINTAAN SLIK OJK ASURANSI KREDIT DAN SURETYSHIP
DOI: 10.23729/fd-0d1e5d70-093b-323b-a0a2-82d25ba5ffbd
title: Finnish Environment Institute snow course data from 2004 to 2024 and subset of longer time series
title: Suomen Ympäristökeskuksen lumilinja aineisto talvesta 2003/2004 talveen 2023/2024 ja joukko pitkiä aikasarjoja alkaen 1940-luvulta

description: The data includes snow course data from Finland covering winters 2004/05 to 2023/24 and 14 quality checked longer timeseries starting from the 1940’s.

The data consist of snow water equivalent (swe), snow depth, and density observations. For the long snow courses, additional observations are made, including fraction of snow free-area, slope/topography, land use type, forest density, and ice on ground. For all snow course observations spatially representative mean values of swe and snow density are provided.

Please reference the data as Finnish Environment Institute snow course data.
description: Aineisto koostuu lumililnjahavainnoista talvilta 2003/2004 - 2023/2024, sekä lisäksi useita pitempiä aikasarjoja alkaen 1940 -luvulta.

Havainnot sisältävät mittauksia lumen vesiarvosta, syvyydestä ja tiheydestä. Pitkiltä lumilinjoilta on lisäksi haivannot mittauspistekohtaisesta pälvisyydestä, maastotyypistä, metsäntiheydestä, rinteen jyrkkyydestä ja suunnasta sekä maan pinnan jääkerroksen paksuudesta. Kaikista lumilinjahavainnoista on laskettu mittauspäivä ja paikka kohtainen alueellisesti edustava lumen vesiarvo ja tiheys.

Käytettäessä viittaa Suomen Ympäristökeskuksen lumilinja aineistoon.
DOI: 10.18150/syxh2f
title: Raw data for project: Gel polymer electrolytes with biodegradable matrix for lithium-ion and sodium-ion batteries

description: Raw data for project: Gel polymer electrolytes with biodegradable matrix for lithium-ion and sodium-ion batteries - funded by the Naional Science Center under the call MINIATURA-6 (Grant No 2022/06/X/ST5/00892).The data set contains the following:1) the raw SEM images (scanning electron miscroscope) the selected gel polymer electrolytes with modified polymer matrix (hybrid matrix made of synthetic polymer and biopolymer in different mass ratios - given in the dataset). Magnitude of 5000x, accelerating voltage 10 kV. Data in tif. format. Related to publication: A. Gabryelczyk, A. Swiderska-Mocek, Tailoring the Properties of Gel Polymer Electrolytes for Sodium-Ion Batteries Using Ionic Liquids: A Review, Chemistry - A European Journal, 30(27), (2024) 2202304207.2) the raw results of thermogravimetric analysis (TGA) of the selected gel polymer electrolytes with modified polymer matrix (hybrid matrix made of synthetic polymer and biopolymer in different mass ratios - given in the dataset). Data in xml. format.Temperature range of the measurement: 30-700 °CTemperature step: 10 °C/min.Atmosphere: nitrogen gas flow, 250 mL/min.Sample mass: 9-14 mg3) the raw project-related data to the manuscript entitled "Biodegradable hybrid polymer matrix based on starch for gel polymer electrolytes – exploring alternatives for sustainable sodium-ion batteries".The data set contains unprocessed results related to the following experiments: biodegradability records, cycling performance of Na-based battery, dimensional shrinkage test, differential scanning calorimetry (DSC) of the gel polymer electrolytes, electrochemical window of the gel polymer electrolytes, Ionic conductivity of the gel polymer electrolytes, SEM images of the gel polymer electrolytes, and TGA of the gel polymer electrolytes (operating conditions are in each specific file in the zip. folder).
DOI: 10.15468/dl.yer9wj
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mauginiella",
 "HasCoordinate is true"
 ]
}

 The dataset includes 9 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001771-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.26fjdu
title: Occurrence Download

description: A dataset containing 91 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Spermospora",
 "HasCoordinate is true"
 ]
}

 The dataset includes 91 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001772-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6cjm44
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Stigmella",
 "HasCoordinate is true"
 ]
}

 The dataset includes 21 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001773-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vwvhcb
title: Occurrence Download

description: A dataset containing 1183 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lecanosticta",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1183 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001774-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ywbv76
title: Occurrence Download

description: A dataset containing 73 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Beniowskia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 73 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001775-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17667886
title: Dataset for "Parameter-Aware Ensemble SINDy with Dimensional Filtering: Application to Subgrid-Scale Closure"

description: Dataset for “Parameter-Aware Ensemble SINDy with Dimensional Filtering: Application to Subgrid-Scale Closure”


This repository provides the postprocessed datasets used to generate the figures and quantitative results in the manuscript Parameter-Aware Ensemble SINDy with Dimensional Filtering.


Contents


Sheet 1 - Sample Case (Heat Diffusion).csv

A sample reference solution for a heat diffusion problem.


Sheet 2 - Sample Case (Burgers).csv

A sample reference solution for a Burgers equation problem.


Sheet 3 - Sample Case (KdV–Burgers).csv

A sample reference solution for a KdV–Burgers system.


Note: All sample cases correspond to the same case index and therefore share consistent random seed and initial condition structure.


Sheet 4 - Two Stages KdV.csv

Two-stage SINDy regression results for the KdV–Burgers system. Includes both first and second stage coefficients for reproducing the bar plots in the manuscript.


Sheet 5 - SGS Heatmap (Sine).csv

Reference Burgers solution (sine initial condition) with SGS model outputs including SINDy SGS predictions.


Sheet 6 - SGS Heatmap (Cubic).csv

Reference Burgers solution (cubic sine initial condition) with SGS model outputs including SINDy SGS predictions.


Sheet 7 - SGS Line (Sine).csv

Linewise SGS comparison at t = 0.5 for the sine case.


Sheet 8 - SGS Line (Cubic).csv

Linewise SGS comparison at t = 0.5 for the cubic sine case.


Sheet 9 - SGS Model Comparison.csv

Metric comparison (MAE, MSE, R2) of SGS models across all Perlin noise-based test cases.


Plotting


All datasets are provided in CSV format and can be plotted using any standard environment including Python or MATLAB. The published figures were generated using DataGraph on macOS.


Notes on Code Availability


The complete data generation and modelling pipeline forms part of an active research line extending this work to higher-dimensional and reacting-flow systems. To protect this ongoing work, the full codebase is not released at this stage. The datasets provided here are sufficient for full reproduction of the results reported in the manuscript.


Contact


For questions regarding dataset structure or reproducibility, please contact

Hanseul Kang

Aalto University

Email: hanseul.kang@aalto.fi
DOI: 10.5281/zenodo.17667885
title: Dataset for "Parameter-Aware Ensemble SINDy with Dimensional Filtering: Application to Subgrid-Scale Closure"

description: Dataset for “Parameter-Aware Ensemble SINDy with Dimensional Filtering: Application to Subgrid-Scale Closure”


This repository provides the postprocessed datasets used to generate the figures and quantitative results in the manuscript Parameter-Aware Ensemble SINDy with Dimensional Filtering.


Contents


Sheet 1 - Sample Case (Heat Diffusion).csv

A sample reference solution for a heat diffusion problem.


Sheet 2 - Sample Case (Burgers).csv

A sample reference solution for a Burgers equation problem.


Sheet 3 - Sample Case (KdV–Burgers).csv

A sample reference solution for a KdV–Burgers system.


Note: All sample cases correspond to the same case index and therefore share consistent random seed and initial condition structure.


Sheet 4 - Two Stages KdV.csv

Two-stage SINDy regression results for the KdV–Burgers system. Includes both first and second stage coefficients for reproducing the bar plots in the manuscript.


Sheet 5 - SGS Heatmap (Sine).csv

Reference Burgers solution (sine initial condition) with SGS model outputs including SINDy SGS predictions.


Sheet 6 - SGS Heatmap (Cubic).csv

Reference Burgers solution (cubic sine initial condition) with SGS model outputs including SINDy SGS predictions.


Sheet 7 - SGS Line (Sine).csv

Linewise SGS comparison at t = 0.5 for the sine case.


Sheet 8 - SGS Line (Cubic).csv

Linewise SGS comparison at t = 0.5 for the cubic sine case.


Sheet 9 - SGS Model Comparison.csv

Metric comparison (MAE, MSE, R2) of SGS models across all Perlin noise-based test cases.


Plotting


All datasets are provided in CSV format and can be plotted using any standard environment including Python or MATLAB. The published figures were generated using DataGraph on macOS.


Notes on Code Availability


The complete data generation and modelling pipeline forms part of an active research line extending this work to higher-dimensional and reacting-flow systems. To protect this ongoing work, the full codebase is not released at this stage. The datasets provided here are sufficient for full reproduction of the results reported in the manuscript.


Contact


For questions regarding dataset structure or reproducibility, please contact

Hanseul Kang

Aalto University

Email: hanseul.kang@aalto.fi
DOI: 10.15468/dl.c3eab9
title: Occurrence Download

description: A dataset containing 12011 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Papilionidae)",
 "Country is one of (China)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12011 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001776-251120083545085/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.30136549
title: <b>Pan-genome assembly of Vine Tea (</b><b><i>Nekemias grossedentata</i></b><b>) reveals structural variation in its dihydromyricetin biosynthesis diversity</b>

description: This dataset provides the genome assemblies and annotations of two accessions of <i>Nekemias grossedentata</i> (vine tea). The data include the assembled genome sequences in FASTA format and the corresponding genome annotations in GFF format. The LY accession is mainly cultivated in Zhangjiajie, Hunan Province, China, and is characterized by its green leaves, while the HY accession originates from Lianzhou, Guangdong Province, China, and is characterized by its red leaves.
DOI: 10.6084/m9.figshare.30136549.v3
title: <b>Pan-genome assembly of Vine Tea (</b><b><i>Nekemias grossedentata</i></b><b>) reveals structural variation in its dihydromyricetin biosynthesis diversity</b>

description: This dataset provides the genome assemblies and annotations of two accessions of <i>Nekemias grossedentata</i> (vine tea). The data include the assembled genome sequences in FASTA format and the corresponding genome annotations in GFF format. The LY accession is mainly cultivated in Zhangjiajie, Hunan Province, China, and is characterized by its green leaves, while the HY accession originates from Lianzhou, Guangdong Province, China, and is characterized by its red leaves.
DOI: 10.6084/m9.figshare.30136549.v2
title: <b>Pan-genome assembly of Vine Tea (</b><b><i>Nekemias grossedentata</i></b><b>) reveals structural variation in its dihydromyricetin biosynthesis diversity</b>

description: This dataset provides the genome assemblies and annotations of two accessions of <i>Nekemias grossedentata</i> (vine tea). The data include the assembled genome sequences in FASTA format and the corresponding genome annotations in GFF format. The LY accession is mainly cultivated in Zhangjiajie, Hunan Province, China, and is characterized by its green leaves, while the HY accession originates from Lianzhou, Guangdong Province, China, and is characterized by its red leaves.