cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.8xbzgg
title: Occurrence Download

description: A dataset containing 44458 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-75.2728608000000037 39.9893106999999972, -75.2728608000000037 39.9933203800000001, -75.2728608000000037 39.9967572600000025, -75.2728608000000037 40.0019125600000010, -75.2728608000000037 40.0076406800000015, -75.2728608000000037 40.0136552100000031, -75.2728608000000037 40.0179513000000000, -75.2645571300000000 40.0179513000000000, -75.2596895100000012 40.0179513000000000, -75.2513859200000041 40.0179513000000000, -75.2468046200000060 40.0179513000000000, -75.2422233300000016 40.0179513000000000, -75.2359240499999942 40.0179513000000000, -75.2273341300000027 40.0179513000000000, -75.2233255000000014 40.0179513000000000, -75.2178852100000057 40.0179513000000000, -75.2118722700000006 40.0179513000000000, -75.2072909000000038 40.0179513000000000, -75.2072909000000038 40.0107911500000029, -75.2072909000000038 40.0044902200000010, -75.2072909000000038 40.0001941299999970, -75.2072909000000038 39.9964708500000015, -75.2072909000000038 39.9893106999999972, -75.2141629099999989 39.9893106999999972, -75.2216075099999983 39.9893106999999972, -75.2273341300000027 39.9893106999999972, -75.2313427600000040 39.9893106999999972, -75.2367830499999997 39.9893106999999972, -75.2407916800000010 39.9893106999999972, -75.2493816000000066 39.9893106999999972, -75.2553945500000054 39.9893106999999972, -75.2628391500000049 39.9893106999999972, -75.2682794300000069 39.9893106999999972, -75.2728608000000037 39.9893106999999972))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 44458 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0099643-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j2vqgb
title: Occurrence Download

description: A dataset containing 26397 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Euphorbia variabilis Ces., Euphorbia esula L., Euphorbia virgata Noë ex Nyman, 1881)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 26397 records from 226 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0240553-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nrvfez
title: Occurrence Download

description: A dataset containing 331 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Stellaria hebecalyx Fenzl"
 ]
}

 The dataset includes 331 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0142959-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8m26vt
title: Occurrence Download

description: A dataset containing 4109 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((-122.69139 49.03541,-122.67728 49.03541,-122.67728 49.04209,-122.69139 49.04209,-122.69139 49.03541))",
 "Geometry POLYGON((-122.67962 49.03543,-122.67644 49.03543,-122.67644 49.04209,-122.67962 49.04209,-122.67962 49.03543))",
 "Geometry POLYGON((-122.69139 49.03329,-122.67841 49.03329,-122.67841 49.0425,-122.69139 49.0425,-122.69139 49.03329))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 4109 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0121648-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kq9fre
title: Occurrence Download

description: A dataset containing 1286 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Allium validum S.Watson",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1286 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061700-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eyzfb8
title: Occurrence Download

description: A dataset containing 702 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Occurrence evidence, Living Specimen, Specimen, Material sample, Human Observation, Machine Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Chrysocyon brachyurus (Illiger, 1815)"
 ]
}

 The dataset includes 702 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0136075-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9jvdqm
title: Occurrence Download

description: A dataset containing 121741 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cracidae"
 ]
}

 The dataset includes 121741 records from 326 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015059-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jgbjg3
title: Occurrence Download

description: A dataset containing 190 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Angraecum distichum Lindl.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 190 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043395-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3s7ekz
title: Occurrence Download

description: A dataset containing 364881 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rabelera holostea (L.) M.T.Sharples & E.A.Tripp"
 ]
}

 The dataset includes 364881 records from 1676 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0142963-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14459/2025mp1782464
title: Novel Dataset of RGB-D Images for Robotic Harvesting of Green Asparagus

description: Enabling robotic harvesting of green asparagus requires the robust detection and
localization of asparagus spears in the field. The dataset contains typical environmental measurement impact, such as a variety of natural spear patterns, weeds, natural lighting, and the effect of ground irregularities. From 7 green asparagus sites located in Germany and France approximately 20 m of one bed of each site were captured with a camera in top down position, perpendicular to the ground. 
The dataset contains RGB images and corresponding depth recorded from the video stream of a IntelRealsense D405 camera. The images have 1280 x 720 pixel resolution and 0.1 mm depth resolution. The average ground distance is around 500 mm. Driving speed around 300 mm/s or above and a frame rate of 30 fps result in approximately 1800 RGB and depth image pairs per site. RGB images are provided in CV_8UC3 png format, the depth map in CV_16UC1 png format.The file readme.txt shares details of the folder structure and file formats.
DOI: 10.71947/arim.jpmxp1222ws0004-5
title: 成膜装置による膜特性の差異確認(2022年度:PD-220)
DOI: 10.71947/arim.jpmxp1222ws0004-6
title: 成膜装置による膜特性の差異確認(2022年度:iHR320)
DOI: 10.6084/m9.figshare.29300927
title: Detrital apatite fission-track (AFT) data

description: Detrital apatite fission-track (AFT) data along the Yarlung River
DOI: 10.6084/m9.figshare.29300927.v1
title: Detrital apatite fission-track (AFT) data

description: Detrital apatite fission-track (AFT) data along the Yarlung River
DOI: 10.5281/zenodo.15646078
title: BIGBIGWIG
DOI: 10.5281/zenodo.15646079
title: BIGBIGWIG
DOI: 10.15468/dl.sdrv4u
title: Occurrence Download

description: A dataset containing 5635 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Salvinia natans (L.) All."
 ]
}

 The dataset includes 5635 records from 260 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0117740-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15646130
title: GM12878 H3K4ME3
DOI: 10.5281/zenodo.15646131
title: GM12878 H3K4ME3
DOI: 10.5281/zenodo.15646146
title: Differential metabolites in AQP5+ and AQP5- gastric cancer cells identified by untargeted metabolomics analyses
DOI: 10.5281/zenodo.15646147
title: Differential metabolites in AQP5+ and AQP5- gastric cancer cells identified by untargeted metabolomics analyses
DOI: 10.6084/m9.figshare.28152035
title: <b>Chinese Seed Trait Database: A curated resource for diaspore traits in the Chinese flora</b>

description: This is a curated repository that compiles an extensive array of diaspore traits for plant species in China — Chinese Seed Trait Database (CSTD). It has so far been assembled from 694 sources in the Chinese language, comprises more than 110,000 records across 118 seed traits for 3,897 plant species. The data spans all major axes of the seed trait spectrum, encompassing morphological, quantitative, phenological, physiological, chemical, and dispersal traits. This initiative overcomes language barriers and enhances the completeness of global seed trait data, ultimately providing an invaluable resource for advancing large-scale ecological research.
DOI: 10.6084/m9.figshare.28152035.v4
title: <b>Chinese Seed Trait Database: A curated resource for diaspore traits in the Chinese flora</b>

description: This is a curated repository that compiles an extensive array of diaspore traits for plant species in China — Chinese Seed Trait Database (CSTD). It has so far been assembled from 694 sources in the Chinese language, comprises more than 110,000 records across 118 seed traits for 3,897 plant species. The data spans all major axes of the seed trait spectrum, encompassing morphological, quantitative, phenological, physiological, chemical, and dispersal traits. This initiative overcomes language barriers and enhances the completeness of global seed trait data, ultimately providing an invaluable resource for advancing large-scale ecological research.
DOI: 10.6084/m9.figshare.28152035.v3
title: <b>Chinese Seed Trait Database: A curated resource for diaspore traits in the Chinese flora</b>

description: This is a curated repository that compiles an extensive array of diaspore traits for plant species in China -- Chinese Seed Trait Database ( CSTD ). It has so far been assembled from 694 sources in the Chinese language, comprises more than 110,000 records across 118 seed traits for 3,897 plant species. The data spans all major axes of the seed trait spectrum, encompassing morphological, quantitative, phenological, physiological, chemical, and dispersal traits. This initiative overcomes language barriers and enhances the completeness of global seed trait data, ultimately providing an invaluable resource for advancing large-scale ecological research.
DOI: 10.17632/kk9b7g3nv9
title: ChewNet: Dataset for Invivo and Invitro Beef and Plant-based Burger Patty Boluses

description: This dataset examines the chewing dynamics of beef and plant-based burger patties using both human (InVivo) and robotic (InVitro) methods, aiming to (1) identify the optimal robotic chewing cycles that mimic human swallowing and (2) extract bolus texture properties via deep learning-based image analysis. For in vivo trials, three healthy male participants provided near-swallow bolus samples, imaged with a 12MP camera and flatbed scanner, followed by Texture Profile Analysis (TPA). In vitro tests used a 3-DOF chewing robot (ChewBot) with adjustable molar trajectories, artificial saliva (10% food weight), and up to 40 chewing cycles with images, force profiles (100ms intervals), and TPA metrics (after every 5 cycles). ChewNet Dataset is organised into InVivo and InVitro folders, which are crucial for food science research (optimising texture in meat analogues), development of artificial mastication systems for food image processing tasks, and analysing in vitro food bolus properties at the swallowing stage.
DOI: 10.17632/kk9b7g3nv9.2
title: ChewNet: Dataset for Invivo and Invitro Beef and Plant-based Burger Patty Boluses

description: This dataset examines the chewing dynamics of beef and plant-based burger patties using both human (InVivo) and robotic (InVitro) methods, aiming to (1) identify the optimal robotic chewing cycles that mimic human swallowing and (2) extract bolus texture properties via deep learning-based image analysis. For in vivo trials, three healthy male participants provided near-swallow bolus samples, imaged with a 12MP camera and flatbed scanner, followed by Texture Profile Analysis (TPA). In vitro tests used a 3-DOF chewing robot (ChewBot) with adjustable molar trajectories, artificial saliva (10% food weight), and up to 40 chewing cycles with images, force profiles (100ms intervals), and TPA metrics (after every 5 cycles). ChewNet Dataset is organised into InVivo and InVitro folders, which are crucial for food science research (optimising texture in meat analogues), development of artificial mastication systems for food image processing tasks, and analysing in vitro food bolus properties at the swallowing stage.
DOI: 10.17632/pfd4g6ts72.1
title: Large-scale phylogenomics untangle the metabolic potential of Picochlorum tauri, a new picoalgal species causing a winter bloom in the Mediterranean Thau lagoon

description: Data repository for Picochlorum tauri , a new picoalgal species causing a winter bloom in the Mediterranean Thau lagoon. In this repository, genome sequences and annotation data can be found. Additionally, comparative genomics analysis results of the interested species with other Trebouxiophyceae are included.
DOI: 10.17632/p6jkzkpdd6.1
title: Tanybase - Combined and Curated Tanycyte Database

description: Tanycytes are ependymal-like glial cells that play a crucial role in regulating the neuroendocrine system, metabolism, and glucose homeostasis. Tanycytes lie in the wall of the third ventricle and coordinate various functions. Traditionally, tanycytes were classified into four subtypes based on their position in the ventricular wall: alpha 1, alpha 2, beta 1 and beta 2 tanycytes. Recent scRNA-seq studies have investigated the role of tanycytes at the transcriptome level, but they fall short due to the limited number of tanycytic cells in the datasets. To address this shortcoming, two prominent databases, Tany-seq and Hypomap, were compiled by combining leading hypothalamus and tanycyte scRNA-seq studies on this topic. However, the number of tanycytes for each subtype and condition was still limited, even after these noble works. To eliminate this pitfall and help future researchers in their quest to identify the role of tanycytes to a greater extent, we combined these two databases into a single mouse tanycyte-specific database called tanybase. Tanybase have a total of 20610 cells from 4 tanycytic subtypes, 5 different diets and 3 different ages. 

In short, tanybase is formed by combining two scRNAseq databases of mouse tanycytes, Hypomap and Tany-seq. Hypomap and Tany-seq databases were combined using shared parameters, including diet, age, tanycyte subclusters, original identity and dataset. Unique cells in each database were combined, and cells with more than 15% mitochondrial transcripts, a total RNA count below 600, and fewer than 200 unique features were removed. We included only cells that were labelled as tanycyte according to the Allen Institute MapMyCells software (RRID:SCR_024672). For integration, tanybase was split into different layers for each dataset containing more than 100 cells and datasets that have less than 100 cells were combined (‘others’). Tanybase was scaled, normalized and variable features were determined using Seurat functions. Principle-component analysis was performed as well as integration for batch correction using canonical correlation analysis. After the integration, layers were re-joined. For dimensionality reduction, we performed UMAP clustering with FindClusters and FindNeighbors functions. Labels were transferred from corresponding databases; unlabelled cells were labelled using module scores and the markers provided in Tany-seq. For Tanybase, we used Seurat (v.5.2.0), AnnData, Matrix packages.
DOI: 10.17632/pdrx7gdsmr
title: Assessing the genotype-by-year effect on training set composition: scripts and dataset

description: This dataset supports the study “Assessing the genotype-by-year effect on training set composition and alternatives to mitigate its impact on genomic selection accuracy.” The research investigates how genotype-by-year (G×Y) interactions influence genomic prediction (GP) accuracy and whether including overlapping checks and progenies in the training set can mitigate these effects.

We hypothesized that limited overlap of entries across years would fail to correct for G×Y effects, reducing selection response. To test this, we conducted stochastic simulations using AlphaSimR, based on the structure of the LSU AgCenter rice breeding program. A total of 36 scenarios were simulated, combining four levels of G×Y interaction (0%, 25%, 50%, 75%) with three levels of overlap (0%, 5%, 10%) for both progenies and checks.

The dataset includes:
 • Input parameters and configuration files for all scenarios
 • R scripts used for simulation and analysis
 • Output data containing genetic parameters: additive variance, population mean, best line performance, and prediction accuracy

Results showed that stronger G×Y interactions consistently reduced GP accuracy and selection gains. Including up to 10% of checks and progenies in the training set did not significantly improve predictive performance. These findings indicate that such overlap is insufficient to account for temporal variation, especially in breeding programs with limited connectivity between cycles.

The dataset enables full reproducibility and can support further research on training set optimization, modeling G×Y interactions, and evaluating selection strategies.
DOI: 10.17632/pdrx7gdsmr.2
title: Assessing the genotype-by-year effect on training set composition: scripts and dataset

description: This dataset supports the study “Assessing the genotype-by-year effect on training set composition and alternatives to mitigate its impact on genomic selection accuracy.” The research investigates how genotype-by-year (G×Y) interactions influence genomic prediction (GP) accuracy and whether including overlapping checks and progenies in the training set can mitigate these effects.

We hypothesized that limited overlap of entries across years would fail to correct for G×Y effects, reducing selection response. To test this, we conducted stochastic simulations using AlphaSimR, based on the structure of the LSU AgCenter rice breeding program. A total of 36 scenarios were simulated, combining four levels of G×Y interaction (0%, 25%, 50%, 75%) with three levels of overlap (0%, 5%, 10%) for both progenies and checks.

The dataset includes:
 • Input parameters and configuration files for all scenarios
 • R scripts used for simulation and analysis
 • Output data containing genetic parameters: additive variance, population mean, best line performance, and prediction accuracy

Results showed that stronger G×Y interactions consistently reduced GP accuracy and selection gains. Including up to 10% of checks and progenies in the training set did not significantly improve predictive performance. These findings indicate that such overlap is insufficient to account for temporal variation, especially in breeding programs with limited connectivity between cycles.

The dataset enables full reproducibility and can support further research on training set optimization, modeling G×Y interactions, and evaluating selection strategies.
DOI: 10.17632/b3d8yxz8r4
title: EXAMINING THE EFFECTS OF EARNINGS MANIPULATION RISK AND FINANCIAL HEALTH DYNAMICS ON MARKET REACTIONS: EVIDENCE FROM INDONESIA STOCK EXCHANGE

description: Financial Statements Data of LQ45 Companies on IDX (2021-2024)
DOI: 10.17632/b3d8yxz8r4.1
title: EXAMINING THE EFFECTS OF EARNINGS MANIPULATION RISK AND FINANCIAL HEALTH DYNAMICS ON MARKET REACTIONS: EVIDENCE FROM INDONESIA STOCK EXCHANGE

description: Financial Statements Data of LQ45 Companies on IDX (2021-2024)