cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18604432
title: SEM Withered Plant (BSE Series) — Kikoh Matsuura (Art–Science Archive)

description: Parent (series) record for *SEM Withered Plant (BSE)* by Kikoh Matsuura.  This record serves as the hub for all child datasets in the series.

**Files included:**- A series overview (TXT) documenting scope, naming rules, citation style, and file policy- A machine-readable index (CSV) that will be updated to list child datasets (DOIs, imaging parameters, etc.)- Withered Plant — Declaration (PDF) — issued once / no future revisions / no images- Withered Plant: Phase I (DOI 1–100) — Record (PDF) — fixed record / no future revisions

Each child dataset contains raw, uncompressed BMP images (≈10 per set, number varies) acquired with a personally owned TECHNEX TinySEM M3-i using the BSE detector under high-vacuum conditions.  Child records provide detailed READMEs with exact parameters (accelerating voltage, working distance, vacuum, pixel size, field of view, frame time, coating).

This parent provides a stable concept DOI for the entire *SEM Withered Plant (BSE)* series.  Child datasets link back via *IsPartOf*, and this parent enumerates them via *HasPart*.  

*This series visualizes the hidden order and chance in withered plants through SEM-BSE, leaving a unique trace at the boundary between art and science.*
DOI: 10.7910/dvn/1tsrkw
title: Replication Data for: Auditing the Human BioMolecular Atlas Program (HuBMAP) Human Reference Atlas (HRA): An Evaluation of Core Digital Objects

description: This dataset contains the audit instruments and evaluation results from the first independent third-party audit of the Human Reference Atlas (HRA), produced by the Human BioMolecular Atlas Program (HuBMAP). The audit was conducted iteratively between March 2024 and August 2025 using publicly accessible data from HRA v2.1 (7th release). The dataset includes: (1) Row-by-row metadata compliance evaluation of 34 ASCT+B tables; (2) Style guide conformance assessment of 22 2D FTU illustrations; (3) Functional usability evaluation of 30 3D Reference Objects; (4) Required field completeness audit of 21 OMAPs; (5) Excel formulas for ASCT+B structural integrity validation; and (6) Row-level presence and formatting compliance evaluation of 34 ASCT+B tables.
description: Audit findings reflect the state of HRA v2.1 (7th release) at the time of evaluation. Structural contiguity violations were identified in three ASCT+B tables (kidney, thymus, ureter) and biomarker depth incompleteness was identified in three organs (kidney, large intestine, liver). All issues were communicated to the HuBMAP team and corrected in HRA v2.3. This dataset documents the audit methodology and findings as a contribution to data quality assessment practices for large-scale biomedical data infrastructure.
DOI: 10.5281/zenodo.18603649
title: Full Transcriptome Analysis Data of M1 and NP in DF-1 Cells

description: Description: This dataset contains the comprehensive RNA-sequencing analysis results for DF-1 cells expressing influenza viral proteins (M1 and NP). The uploaded file includes:





Complete DEG Tables: All analyzed genes with their respective Fold Change (log2), raw p-values, and BH-adjusted p-values.




Count Matrix: Raw read counts and normalized values (FPKM, TPM) for each sample.




Functional Annotation: Significant Gene Ontology (GO) terms and KEGG pathway enrichment analysis results derived from the DEGs.
DOI: 10.48580/dgw9g.v5
title: Overview of Campopleginae (Hymenoptera: Ichneumonidae) species described from 2016 to 2025 with revised taxon metrics
DOI: 10.48580/dgw9g.v6
title: Overview of Campopleginae (Hymenoptera: Ichneumonidae) species described from 2016 to 2025 with revised taxon metrics
DOI: 10.15468/dl.stwa9z
title: Occurrence Download

description: A dataset containing 24689 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mesosphaerum suaveolens",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 24689 records from 364 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007399-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nu8u7u
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Miersia humilis",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 5 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007401-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jxg7ny
title: Occurrence Download

description: A dataset listing the 1685 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is IDN.9.14_1",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 1685 records were derived from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007400-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18604452
title: Dataset for Explainable AI Framework Study

description: This repository contains the dataset supporting the experimental evaluation reported in the manuscript.
DOI: 10.5281/zenodo.18604453
title: Dataset for Explainable AI Framework Study

description: This repository contains the dataset supporting the experimental evaluation reported in the manuscript.
DOI: 10.15468/dl.2uycr7
title: Occurrence Download

description: A dataset containing 365773 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 174c6da2-e002-42fe-9f56-2f9d670240f4",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Locality is not null"
 ]
}

 The dataset includes 365773 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007406-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.epjyav
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leptuca umbratila"
 ]
}

 The dataset includes 26 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007402-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v2kn8t
title: Occurrence Download

description: A dataset containing 436353 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 4cadac10-3e7b-11d9-8439-b8a03c50a862",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Locality is not null"
 ]
}

 The dataset includes 436353 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007405-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cpmnau
title: Occurrence Download

description: A dataset containing 173530 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 352bdfe0-c57b-11dd-a8eb-b8a03c50a862",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Locality is not null"
 ]
}

 The dataset includes 173530 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007403-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.33ba5c
title: Occurrence Download

description: A dataset containing 3255 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Korea, Republic of",
 "Geometry POLYGON((127.13206 37.5104,127.16863 37.5104,127.16863 37.55723,127.13206 37.55723,127.13206 37.5104))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 3255 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007404-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.spyjgw
title: Occurrence Download

description: A dataset containing 934 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carnegiella strigata",
 "DecimalLatitude is not null",
 "DecimalLongitude is not null"
 ]
}

 The dataset includes 934 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007408-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18604474
title: xTB Optimized Structures for Kinetic Resolution
DOI: 10.5281/zenodo.18604473
title: xTB Optimized Structures for Kinetic Resolution
DOI: 10.15468/dl.bq7v8g
title: Occurrence Download

description: A dataset containing 14852021 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 14852021 records from 2725 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007387-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/58ybs5zxcw.1
title: CHANGING CONTOURS OF ABORTION JURISPRUDENCE, WOMEN CONSENT IN THE WAKE OF THE MEDICAL TERMINATION OF PREGNANCY (AMENDMENT) ACT, 2021v

description: India, sees death of approximately 10 pregnant women per day because of an unsafe abortion practice. This number, however, is usually higher decades ago than what it is today. The Shantilal Shah Committee, created in 1964 entrusted with task of working out a liberal and safest approach for adoption practices to fight with rising unsafe deadly abortions in the country and on report of committee “The Medical Termination of Pregnancy Act, 1971” was passed subsequently to tackle the menace rising death. Recently parliament passed Amendment to the 1971, Act in 2021, seeking to further ease up and enlarge the horizon of lawful abortion. This Act itself and subsequent amendment over the years brings approaches in tune with making abortion accessible, lawful and secure. Nevertheless, the fineness of law does not inevitably correlate with the quality of deliverance. India’s healthcare sphere has a plethora of drawbacks which more frequently challenge the progressive policies adopted by the state. There are also the controversial issues of abortion for adolescents, as well as the notion that abortion should be a woman’s choice. This piecemeal of writing endeavors to investigate the Indian abortion regime in the wake of aforementioned issues, by looking into forces of infrastructure, social disgrace and convergence of medical and patriarchal prejudice underestimate the good that regulation can do.
DOI: 10.17632/rjr2jvhdfy.1
title: MLD-BD: A Comprehensive Image Dataset for Mango Leaf Disease Detection in Bangladesh

description: The "MLD-BD" dataset is a primary and augmented image dataset specifically curated for mango leaf disease identification and classification, collected from major mango-producing regions in Bangladesh, namely Rajshahi, Chapainawabganj, and Mymensingh. Mango cultivation plays a vital role in the agricultural economy of Bangladesh; however, diseases affecting mango leaves significantly impact production yield and quality. Thus, timely and precise detection is crucial for effective disease management and control measures.

Dataset Overview:

This dataset comprises a total of 9,000 images, systematically organized into two subsets:

Primary (Original) Dataset: Consisting of 3,000 images, with each class containing 600 original images captured directly from the fields.

Augmented Dataset: This subset comprises 6,000 images, with each class having 1,200 images, generated through various data augmentation techniques, including rotation, flipping, scaling, translation, brightness adjustments, and noise addition. This augmentation ensures a diverse representation of each disease, helping improve the robustness and generalization capabilities of machine learning and deep learning models.

Classes:

The dataset covers 5 distinct classes of mango leaf conditions, crucial for practical agricultural applications:

Anthracnose: A fungal disease causing dark, sunken lesions on leaves, severely impacting mango production.

Bacterial Canker: A bacterial infection characterized by water-soaked lesions leading to leaf necrosis and branch dieback.

Die Back: Fungal-induced disease causing progressive death of branches, noticeable leaf browning, and drying.

Gall Midge: Insect infestation leading to abnormal leaf growth, curled leaf structures, and deformation.

Healthy: Images representing disease-free mango leaves for comparative and control purposes.

Data Collection Methodology:

Images were captured using high-resolution smartphone cameras under natural environmental conditions to ensure real-world variability, including different lighting conditions, angles, and backgrounds. Data collection spanned multiple mango orchards across the selected geographical locations to ensure extensive diversity and representativeness.

Regions Covered: Rajshahi, Chapainawabganj, and Mymensingh, Bangladesh.

Image Resolution: Standardized to a resolution suitable for training machine learning models 512×512 pixels.

Format: JPG format, optimized for computational efficiency and easy integration with popular deep learning frameworks.

Applications:

Automated mango leaf disease identification.

Comparative analysis of machine learning and deep learning models.

Development and evaluation of image-processing techniques in precision agriculture.

Usage and Accessibility:

This dataset will be publicly available on Mendeley Data, ensuring easy accessibility and utilization by researchers, data scientists, agriculturists, and practitioners in agricultural informatics.
DOI: 10.17632/rjr2jvhdfy.2
title: MLD-BD: A Comprehensive Image Dataset for Mango Leaf Disease Detection in Bangladesh

description: The "MLD-BD" dataset is a primary and augmented image dataset specifically curated for mango leaf disease identification and classification, collected from major mango-producing regions in Bangladesh, namely Rajshahi, Chapainawabganj, and Mymensingh. Mango cultivation plays a vital role in the agricultural economy of Bangladesh; however, diseases affecting mango leaves significantly impact production yield and quality. Thus, timely and precise detection is crucial for effective disease management and control measures.

Dataset Overview:

This dataset comprises a total of 9,000 images, systematically organized into two subsets:

Primary (Original) Dataset: Consisting of 3,000 images, with each class containing 600 original images captured directly from the fields.

Augmented Dataset: This subset comprises 6,000 images, with each class having 1,200 images, generated through various data augmentation techniques, including rotation, flipping, scaling, translation, brightness adjustments, and noise addition. This augmentation ensures a diverse representation of each disease, helping improve the robustness and generalization capabilities of machine learning and deep learning models.

Classes:

The dataset covers 5 distinct classes of mango leaf conditions, crucial for practical agricultural applications:

Anthracnose: A fungal disease causing dark, sunken lesions on leaves, severely impacting mango production.

Bacterial Canker: A bacterial infection characterized by water-soaked lesions leading to leaf necrosis and branch dieback.

Die Back: Fungal-induced disease causing progressive death of branches, noticeable leaf browning, and drying.

Gall Midge: Insect infestation leading to abnormal leaf growth, curled leaf structures, and deformation.

Healthy: Images representing disease-free mango leaves for comparative and control purposes.

Data Collection Methodology:

Images were captured using high-resolution smartphone cameras under natural environmental conditions to ensure real-world variability, including different lighting conditions, angles, and backgrounds. Data collection spanned multiple mango orchards across the selected geographical locations to ensure extensive diversity and representativeness.

Regions Covered: Rajshahi, Chapainawabganj, and Mymensingh, Bangladesh.

Image Resolution: Standardized to a resolution suitable for training machine learning models 512×512 pixels.

Format: JPG format, optimized for computational efficiency and easy integration with popular deep learning frameworks.

Applications:

Automated mango leaf disease identification.

Comparative analysis of machine learning and deep learning models.

Development and evaluation of image-processing techniques in precision agriculture.

Usage and Accessibility:

This dataset will be publicly available on Mendeley Data, ensuring easy accessibility and utilization by researchers, data scientists, agriculturists, and practitioners in agricultural informatics.
DOI: 10.17632/xbyt6x8dg7
title: Liujiang River

description: Heavy metals and pahs
DOI: 10.17632/xbyt6x8dg7.1
title: Liujiang River

description: Heavy metals and pahs
DOI: 10.15468/dl.cfawh7
title: Occurrence Download

description: A dataset containing 321995 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Triticum aestivum, Oryza sativa, Hordeum vulgare, Vigna radiata, Ulmus pumila, Sorghum bicolor, Prunus persica, Cucumis melo, Castanea mollissima, Diospyros kaki, Phaseolus vulgaris, Vigna unguiculata, Zea mays, Prunus armeniaca, Sesamum indicum, Raphanus sativus, Vigna angularis, Setaria italica, Pisum sativum, Medicago sativa, Brassica rapa glabra, Citrullus lanatus, Pseudocydonia sinensis, Ziziphus jujuba, Juglans regia, Litchi chinensis, Cucurbita moschata, Avena sativa, Cucumis sativus, Cucurbita pepo, Helianthus annuus, Vigna unguiculata sesquipedalis, Panicum miliaceum, Vernicia montana, Prunus mume, Vicia faba, Cannabis sativa, Capsicum annuum, Citrus maxima, Elymus pseudocaninus, Solanum lycopersicum, Spinacia oleracea, Arachis hypogaea, Benincasa hispida, Lactuca sativa, Allium cepa, Solanum melongena, Agropyron cristatum, Lablab purpureus, Pyrus ussuriensis, Crataegus pinnatifida, Lagenaria siceraria, Daucus carota, Diospyros lotus, Pyrus calleryana, Vitis vinifera, Citrus sinensis, Colocasia esculenta, Brassica juncea, Citrus reticulata, Castanea henryi, Pinus bungeana, Beta vulgaris, Fagopyrum lineare, Gossypium arboreum, Agropyron sibiricum, Callistephus chinensis, Davidia involucrata, Rhododendron crinigerum, Astragalus melilotoides, Prunus tomentosa, Camellia sinensis, Juglans mandshurica, Meconopsis integrifolia, Prunus salicina, Viburnum betulifolium, Apium graveolens, Pistacia chinensis, Prunus davidiana, Calamagrostis epigejos, Gleditsia sinensis, Hibiscus cannabinus, Hordeum vulgare coeleste, Poa sphondylodes, Avena nuda, Malus sylvestris, Phyllostachys nidularia, Pinus armandii, Triticum turgidum, Triticum turgidum durum, Atalantia buxifolia, Berberis wilsoniae, Cucurbita maxima, Brassica oleracea, Fagopyrum esculentum, Vernicia fordii, Vigna unguiculata cylindrica, Actinidia chinensis, Castanea seguinii, Coriandrum sativum)",
 "Country is United States of America",
 "Year is greater than or equal to 1898",
 "Year is less than or equal to 2024",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Human Observation, Specimen, Living Specimen, Occurrence evidence)"
 ]
}

 The dataset includes 321995 records from 315 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034252-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.udgnta
title: Occurrence Download

description: A dataset containing 140 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Prunella vulgaris",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 140 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034271-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/rvy9kkvdmt.1
title: Forecasting Urban Wastewater Microbiome Dynamics Using a Digital Twin Framework

description: Urban wastewater microbiomes are complex and temporally dynamic, offering valuable insight into community-scale microbial
ecology and potential public health trends. However, existing wastewater-based studies often remain descriptive, lacking tools
for predictive modeling. In this study, we introduce a digital twin framework that forecasts microbial abundance trajectories in
urban wastewater using an interpretable generative model, Q-net. Trained on a 30-week longitudinal metagenomic dataset from
seven wastewater treatment plants, the model captures temporal microbial dynamics with high fidelity (R² &gt; 0.97 for key taxa;
R² = 0.998 at the final timepoint). Beyond accurate forecasting, Q-net provides transparent model structure through conditional
inference trees and enables simulation of realistic microbial trends under hypothetical scenarios. This work demonstrates the
potential of digital twins to move wastewater microbiome studies from static snapshots to dynamic, predictive systems, with
broad implications for environmental monitoring and microbial ecosystem modeling
DOI: 10.15468/dl.rmzubd
title: Occurrence Download

description: A dataset containing 407 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rubus steudneri"
 ]
}

 The dataset includes 407 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034273-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hwyqgq
title: Occurrence Download

description: A dataset containing 454 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Limenitis camilla"
 ]
}

 The dataset includes 454 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034274-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qb94sg
title: Occurrence Download

description: A dataset containing 15906 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Prunella vulgaris",
 "Country is Russian Federation",
 "HasCoordinate is true"
 ]
}

 The dataset includes 15906 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034272-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48567/q03h-wa67
title: Cape Bird Automatic Weather Station, 2008 Reader format three-hour observational data.
DOI: 10.48567/x9ee-y277
title: Cape Bird Automatic Weather Station, 2008 quality-controlled observational data.