cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/ds3582v368.4
title: Annex to "Background Values of Trace Metals in the Soil of the Katangan Copperbelt, DR Congo" : https://doi.org/10.25928/5xn1-qq47

description: This dataset compiles measurements of metals in soils collected across the Katangan Copperbelt in the Democratic Republic of Congo. The samples were taken from two soil layers (0-25 cm and 25-50 cm) and systematically classified by lithostratigraphic unit. For each sampling point, the dataset includes geographic coordinates, field observations, and concentrations of a broad suite of elements such as As, Co, Cu, Mn, Ni, Pb, Zn. 
Beyond raw concentrations, the dataset provides an interactive map that brings together all results. Users can select the trace metal of interest (e.g. Cu, Co) and the soil horizon (topsoil: 0–25 cm; subsoil: 25–50 cm), access summary statistics (50th and 90th percentiles, mean, standard deviation, coefficient of variation) and display spatial distribution maps for the Katangan Copperbelt. The interface allows users to query a point by GPS coordinates and view the pedo-geochemical background values and other statistics of the lithostratigraphic unit in which that point lies. It also supports map export for direct inclusion in reports. Available in French, English and German, this interactive map improves accessibility and uptake by stakeholders.
DOI: 10.17632/d98mhx3yy9.1
title: A Multi-Year Dataset of 226 Dune Segments

description: # Dataset Title
Morphometric and Climatic Drivers of Dune Migration: A Multi-Year Dataset of 226 Dune Segments

# Description
This dataset contains morphological, climatic, and kinematic metrics for 226 individual dune segments monitored between 2017 and 2025 in a hyper-active aeolian system. The data was generated to analyze the drivers of dune migration using machine learning (XGBoost) and explainable AI techniques.

# Methodology
* **Dune Extraction:** Dune boundaries were segmented from high-resolution satellite imagery (Sentinel-2, Landsat 8/9) using a dual-stream deep learning model.
* **Migration Tracking:** Migration rates were computed using the COSI-Corr algorithm to measure centroid displacement with sub-pixel accuracy over annual intervals.
* **Topography:** Morphometric variables (width, slope) were derived from the ALOS World 3D-30m (AW3D30) DEM.
* **Climate:** Drift Potential (DP) was calculated from ERA5-Land hourly wind data using the Fryberger method.

# Variables
The dataset (`Seg_Processed.xlsx`) includes the following key variables:
1. `A_Dune_ID`: Unique identifier for each dune segment.
2. `Migration_rate` (m/year): The dependent variable representing the annual rate of dune celerity.
3. `A_width` (m): Dune width, serving as a proxy for dune size/volume (inverse-size scaling).
4. `Slope_Mean` (degrees): Mean stoss slope of the dune segment.
5. `DP_Mean` (vector units): Mean Drift Potential representing wind energy.

# Potential Use Cases
* Benchmarking machine learning models for geomorphic prediction.
* Validating physical scaling laws of sediment transport.
* Analyzing non-linear interactions between dune morphology and wind regime.
* Calibrating global sand transport models.

# Format
* File: `Seg_Processed.xlsx` (Excel format)
* Rows: 226
* Columns: 22
DOI: 10.5281/zenodo.17862878
title: MTA (Malaysian Trash Annotation): In-The-Wild Instance Segmentation Dataset for Waste Segregation

description: Malaysian Trash Annotation or MTA in short is a localised instance segmentation dataset designed to address the current issue of waste segregation in Southeast Asia context. Compare with other openly-sourced dataset, MTA is heavily designed around real-world situation where it provides polygon masking to capture the exact geometry of the trash.

Goal of the project:To provide COCO Segmentation formatted database that capable of distinguish between chemically distinct but visually similar material (PET material and Thermoform) and estimating position of garbage in uncontrolled situation.

Dataset Statistics (As of Version: 08122025)



Task: Instance Segmentation (Polygons)

Classes: 13 (Material-based separation)

Environment: Supermarkets (clean and ideal condition), Roadside (weathered), Food Courts (occluded/deformed).

Hardware: Heterogeneous capture using 5 different devices (Oppo, Honor, Samsung, iPhone, Realme).

Capture Protocol: Aspect Ratio locked at 4:3, Multi-angle (Top, Side, 45-degree) with no AI enhancements and no HDR enabled.


Classes of Dataset (As of Version: 08122025)



101_PET_Bottle: Clear/Tinted bottles (Mineral water, Coke, 5kg Oil bottles).

102_HDPE_Container: Opaque rigid plastics (Detergent, Shampoo).

103_Mixed_Rigid: Thermoformed cups (Bubble tea, Yogurt tubs) - Distinct from PET Bottles.

104_Soft_Plastic: Clean LDPE films, Gardenia loaf bags (captured in both flat and knotted states).

201_Aluminum_Can: Carbonated drink cans (Smooth wall).

202_Tin_Can: Food cans (Ribbed wall, steel).

301_Cardboard: Corrugated boxes, Tissue boxes.

302_Paper: A4, Newspaper, Magazines.

303_TetraPak: Laminated cartons (Milo, Yeos, Juice).

401_Glass: Jars, Sauce bottles.

501_Contaminated: Greasy pizza boxes, dirty containers.

502_General_Trash: Ikat Tepi (fluid bags), Straws, Receipts, Wax-coated wrappers (McDonald's).

601_E_Waste: Cables, Batteries, Vapes.


Devices (As of Version: 08122025)



Oppo Reno 14 MY Version (OppoReno14)

Samsung Note 10 MY Version (SamsungNote10)

Iphone 11 MY Version (Iphone11)

Honor 200 MY Version (Honor200)

Realme 5s MY Version (Realme5s)


Notes:



Reflections: Contains samples on glass/steel tables; polygons are tightly cropped to the object, excluding ghost reflections.

Deformation: Includes crushed cans and flattened bottles to simulate end-of-life object states.

Localization: Features "Ikat Tepi" and "Keropok" wrappers specific to the Malaysian region.
DOI: 10.17632/r8jzxzt28s
title: Micromagnetic modeling of the interaction of single-domain ferromagnetic particles in a nanopowder

description: Supplementary information to the article. Visualized data on magnetization reversal of nanoparticle's clusters.
DOI: 10.17632/r8jzxzt28s.1
title: Micromagnetic modeling of the interaction of single-domain ferromagnetic particles in a nanopowder

description: Supplementary information to the article. Visualized data on magnetization reversal of nanoparticle's clusters.
DOI: 10.15468/dl.egza2x
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is Continent derived from coordinates",
 "TaxonKey is Macrotis leucura"
 ]
}

 The dataset includes 46 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040069-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/rgb77xm3jf.1
title: LSS MRI AISSLab Dataset: Medical Spine Sagittal MRI Dataset for Segmentation and Foraminal Stenosis detection

description: ☐ Dataset:
● The LSS MRI AISSLab Dataset is a comprehensive sagittal lumbar spine MRI collection containing 500 patients with fully curated imaging data, expert clinical annotations, and detailed anatomical segmentation masks for the scientifc purpose (noncommercial). 
● This dataset was approved by the Institutional Review Board (IRB) and clinically validated by neurologist experts at Firat University Hospital. The dataset includes a total of 8,500 sagittal MRI slices and 3,885 bounding-box annotations describing foraminal stenosis across the five lumbar levels (L1–L2 through L5–S1). 
● A total of 1,703 right foraminal stenosis (RFS) and 1,982 left foraminal stenosis (LFS) regions were annotated. Each annotation specifies the lumbar level, anatomical side, and clinically assigned stenosis grade (Normal, Mild, Moderate, Severe). 
● Across all lumbar levels, the dataset includes 1,067 Normal, 1,722 Mild, 1,049 Moderate, and 47 Severe Stenosis cases. Mild stenosis represents the largest proportion of annotations, followed by Normal and Moderate categories, while Severe stenosis is relatively rare. 
● In addition to foraminal labels, the dataset provides expert-refined segmentation masks on the middle sagittal slice for key anatomical structures, including vertebrae, intervertebral discs (IVDs), sacrum, posterior A, posterior B, and the anterior background region. These masks were generated through a combined automated-and-manual refinement workflow and reviewed by neurologists to ensure anatomical accuracy. 
● The dataset is organized into three components: (1) full sagittal DICOM series for each patient; (2) middle-slice images accompanied by pixel-level masks in PNG/XML format; and (3) full-slice PNG images with corresponding stenosis annotations when visible. 

☐ ACKNOWLEDGMENT: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. RS-2023-00256517) and by the TUBITAK (The Scientific and Technological research Council of Turkey) under Grant Number: 123N325. This work was supported by the IITP(Institute of Information & Communications Technology Planning & Evaluation)-ITRC(Information Technology Research Center) grant funded by the Korea government (Ministry of Science and ICT) (IITP-2025-RS-2024-00437191).

☐ Please cite these articles:
[1] Salem, Saied, Afnan Habib, Mukhlis Raza, Zaid Al-Huda, Omar Al-maqtari, Bilal Ertuğrul, Özal Yıldırım, Yeong Hyeon Gu, and Mugahed A. Al-antari. "AutoSpineAI: Lightweight Multimodal CAD Framework for Lumbar Spine MRI Assessments." In IEEE-EMBS International Conference on Biomedical and Health Informatics 2025.

[2] Al-Antari, Mugahed A., Saied Salem, Mukhlis Raza, Ahmed S. Elbadawy, Ertan Bütün, Ahmet Arif Aydin, Murat Aydoğan, Bilal Ertuğrul, Muhammed Talo, and Yeong Hyeon Gu. "Evaluating AI-powered predictive solutions for MRI in lumbar spinal stenosis: a systematic review." Artificial Intelligence Review 58, no. 8 (2025): 221.
DOI: 10.17632/s87ytk6ghn
title: Toxin candidates identified by DeTox in the paired-end transcriptome of the deep-sea zoanthid Zibrowius primnoidus

description: This dataset contains outputs generated by “DeTox: a pipeline for the detection of toxins in venomous organisms” applied to the paired-end transcriptome assembly of the deep-sea zoanthid Zibrowius primnoidus. It includes both toxin candidate files and key intermediate DeTox outputs derived from the RNA-seq data.

The dataset includes the following files:

• DeTox_Zibrowius_primnoidus_candidate_toxins.fasta: FASTA file containing amino acid sequences of toxin candidates identified in the transcriptome of Zibrowius primnoidus by DeTox.

• DeTox_Zibrowius_primnoidus_toxins.tsv: TSV file providing detailed annotations and information on the toxin candidates, including similarity- and domain-based evidence where available.

• DeTox_Zibrowius_primnoidus.faa: amino acid sequences of all ORFs predicted by DeTox (via orfipy) from the paired-end transcriptome of Zibrowius primnoidus.

• DeTox_Zibrowius_primnoidus.clustered.faa: non-redundant amino acid sequences obtained by clustering DeTox_Zibrowius_primnoidus.faa with CD-HIT at 0.99 sequence identity, used to reduce redundancy before downstream analyses.

• DeTox_output_Zibrowius_primnoidus.orfs_dna.fa: nucleotide sequences of the ORFs corresponding 1:1 to the proteins in DeTox_Zibrowius_primnoidus.faa, provided to allow inspection of start/stop codons and coding sequence context.
DOI: 10.17632/s87ytk6ghn.1
title: Toxin candidates identified by DeTox in the paired-end transcriptome of the deep-sea zoanthid Zibrowius primnoidus

description: This dataset contains outputs generated by “DeTox: a pipeline for the detection of toxins in venomous organisms” applied to the paired-end transcriptome assembly of the deep-sea zoanthid Zibrowius primnoidus. It includes both toxin candidate files and key intermediate DeTox outputs derived from the RNA-seq data.

The dataset includes the following files:

• DeTox_Zibrowius_primnoidus_candidate_toxins.fasta: FASTA file containing amino acid sequences of toxin candidates identified in the transcriptome of Zibrowius primnoidus by DeTox.

• DeTox_Zibrowius_primnoidus_toxins.tsv: TSV file providing detailed annotations and information on the toxin candidates, including similarity- and domain-based evidence where available.

• DeTox_Zibrowius_primnoidus.faa: amino acid sequences of all ORFs predicted by DeTox (via orfipy) from the paired-end transcriptome of Zibrowius primnoidus.

• DeTox_Zibrowius_primnoidus.clustered.faa: non-redundant amino acid sequences obtained by clustering DeTox_Zibrowius_primnoidus.faa with CD-HIT at 0.99 sequence identity, used to reduce redundancy before downstream analyses.

• DeTox_output_Zibrowius_primnoidus.orfs_dna.fa: nucleotide sequences of the ORFs corresponding 1:1 to the proteins in DeTox_Zibrowius_primnoidus.faa, provided to allow inspection of start/stop codons and coding sequence context.
DOI: 10.15468/dl.3a4ajr
title: Occurrence Download

description: A dataset containing 2789 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bufotes viridis",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2000",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Country is Germany",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 5000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 2789 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040070-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/9838jdjm5b
title: Centennial-scale Burial of Glomalin-related Soil Protein in East China Sea Shelf Sediments

description: This dataset provides the primary data for paper "Centennial-scale Burial of Glomalin-related Soil Protein in East China Sea Shelf Sediments".
DOI: 10.17632/9838jdjm5b.1
title: Centennial-scale Burial of Glomalin-related Soil Protein in East China Sea Shelf Sediments

description: This dataset provides the primary data for paper "Centennial-scale Burial of Glomalin-related Soil Protein in East China Sea Shelf Sediments".
DOI: 10.15468/dl.3cw5un
title: Occurrence Download

description: A dataset containing 986 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tomopteris septentrionalis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 986 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040071-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/umkljg
title: PAN-00181931 - early medieval enamelled disc brooch variant A1

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00181931&lt;/p&gt;
description: Modified: 2025-10-31T08:57:22+01:00
DOI: 10.34894/ezo4je
title: EurekAlert!: An open dataset for science communication research

description: This dataset comprises press releases from the EurekAlert! platform, covering the latest research findings and scientific discoveries across a wide range of academic disciplines. EurekAlert! is a global science news service operated by the American Association for the Advancement of Science (AAAS), dedicated to disseminating scientific news to the public and the media. 

Dataset Coverage: The dataset spans from the inception of the EurekAlert! platform in January 1996 through March 2025, encompassing a total of 566,566 press releases. 

The dataset includes the following basic metadata fields: 
- Euid: The unique identifier of press releases. 
- Title: The title of the press release, providing a concise summary of the main content. - Institution: The name of the institution or research unit that issued the press release.
- Post_time: The date when the press release was published. 
- Description: A brief summary of the press release, highlighting the key information. 
- Keywords: Keywords related to the content of the press release, helping users quickly understand the topic. 
- DOI (Digital Object Identifier): If applicable, the DOI of the research paper mentioned in the press release. 
- Journal: The journal of the research paper. 
- Funder: The funder of the research.
description: 1) Webscrapping of the EurekAlert! website;
2) Consent to publish the dataset of press releases metadata provided by Brian Lin, Director of EurekAlert!.
description: Updated related publication in metadata
DOI: 10.5281/zenodo.17864166
title: Database for "Removal of carbamazepine and diclofenac at trace levels from water using a regenerable polymeric adsorbent and a desorption-based analytical method"
DOI: 10.5281/zenodo.17864167
title: Database for "Removal of carbamazepine and diclofenac at trace levels from water using a regenerable polymeric adsorbent and a desorption-based analytical method"
DOI: 10.17632/czsf8899jm.2
title: Dataset of “Determinants and forecasting of corporate greenwashing behavior”: Corporate greenwashing accusations

description: This dataset accompanies the paper: Jens Eckberg, Gregor Dorfleitner, Manuel C. Kathan, Sebastian Utz; Determinants and forecasting of corporate greenwashing behavior, Journal of Economic Behavior & Organization, Volume 241, 2026, 107354, ISSN 0167-2681, https://doi.org/10.1016/j.jebo.2025.107354

The dataset comprises a list of third-party accusations of greenwashing against STOXX Europe 600 companies, published in the media and on social media platforms, between 2011 and 2023. These accusations were manually collected and the severity of the accusations was assessed by humans based on a predefined framework. The authors raised no accusations; the dataset solely evaluates and codes greenwashing accusations made publicly available by external sources. Each third-party accusation was assessed for its severity. The variable “GW_SCORE” captures this assessment on a scale from 0 (no greenwashing) to 1 (greenwashing). A detailed description of the construction, coding procedure, and validation of the greenwashing severity score is provided in the paper. 

The dataset includes a standard company identifier, specifically GVKEY (Compustat), to facilitate matching with other databases. It is structured as a panel dataset with annual observations for the period 2011–2023. The dataset also contains the column “USED_FOR_ANALYSIS”, which indicates True if a given company-year score was included in the empirical analyses of the paper, and False if it was not. 

Please cite the following studies when using the dataset, as they provide the rationale for its development.

Eckberg, J., Dorfleitner, G., Kathan, M. C., & Utz, S. (2026). Determinants and forecasting of corporate greenwashing behavior. Journal of Economic Behavior & Organization, 241, 107354. https://doi.org/10.1016/j.jebo.2025.107354

Kathan, M. C., Utz, S., Dorfleitner, G., Eckberg, J., & Chmel, L. (2025). What you see is not what you get: ESG scores and greenwashing risk. Finance Research Letters, 74, 106710. https://doi.org/10.1016/j.frl.2024.106710
DOI: 10.17632/nc54gzmnnc
title: Sulfides on the Moon: A Record of Magmatic and Impact Histories
DOI: 10.17632/nc54gzmnnc.1
title: Sulfides on the Moon: A Record of Magmatic and Impact Histories
DOI: 10.15468/dl.g5zm2v
title: Occurrence Download

description: A dataset containing 2249 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "TaxonKey is Ricinus communis",
 "Year 2000-2025"
 ]
}

 The dataset includes 2249 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040072-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2hgpjfry43
title: Pediatric Brucellosis With Negative Serology: Molecular Confirmation and Implications for Epidemiological Surveillance in Mexico

description: Genetic Data (16s rRNA)
DOI: 10.17632/2hgpjfry43.1
title: Pediatric Brucellosis With Negative Serology: Molecular Confirmation and Implications for Epidemiological Surveillance in Mexico

description: Genetic Data (16s rRNA)
DOI: 10.17632/fpfsbxmc9c
title: Replication package for Producing More, Reproducing Less The Demographic Costs of China's Export Success

description: This dataset provides the materials necessary to replicate the empirical analysis in the paper "Producing More, Reproducing Less: The Demographic Costs of China's Export Success".

The replication package contains:
A Readme file with a detailed description of data sources, data files, codes and software requirements.
Publicly available data files.
main_tables.do; figures.do; appendix_tables.do
DOI: 10.17632/fpfsbxmc9c.1
title: Replication package for Producing More, Reproducing Less The Demographic Costs of China's Export Success

description: This dataset provides the materials necessary to replicate the empirical analysis in the paper "Producing More, Reproducing Less: The Demographic Costs of China's Export Success".

The replication package contains:
A Readme file with a detailed description of data sources, data files, codes and software requirements.
Publicly available data files.
main_tables.do; figures.do; appendix_tables.do
DOI: 10.17632/gc2hryw8z9
title: shuwei

description: HA of different structures exerted varying effects on soil carbon cycling
DOI: 10.17632/gc2hryw8z9.1
title: shuwei

description: HA of different structures exerted varying effects on soil carbon cycling
DOI: 10.17026/ar/i8sb4x
title: PAN-00166478 - conical spindle whorl (handmade pottery)

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00166478&lt;/p&gt;
description: Modified: 2025-10-13T10:21:28+02:00
DOI: 10.15468/dl.8nh537
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tomopteris tenuis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040073-251120083545085/datasets/export for details.
DOI: 10.15468/dl.52by2u
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is Continent derived from coordinates",
 "TaxonKey is Notomys amplus"
 ]
}

 The dataset includes 32 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040076-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bdbhxd
title: Occurrence Download

description: A dataset containing 7397 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Octobranchus floriceps",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7397 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040077-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.