cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.c26ygt
title: Occurrence Download

description: A dataset containing 109 records in GBIF matching the query:
SELECT "year", GBIF_EEARGCode( 1000, decimalLatitude, decimalLongitude, COALESCE(coordinateUncertaintyInMeters, 1000) ) AS eeaCellCode, classKey, class, genusKey, genus, COUNT(*) AS occurrences, MIN(COALESCE(coordinateUncertaintyInMeters, 1000)) AS minCoordinateUncertaintyInMeters, MIN(GBIF_TemporalUncertainty(eventDate, null)) AS minTemporalUncertainty FROM occurrence WHERE occurrenceStatus = 'PRESENT' AND genusKey IN (2284443, 2202786, 2161911, 2161467, 7652364, 2176168, 3092125, 2771094, 8782549, 2457378, 2453882, 2457825, 2454645, 2465626, 2466496, 2459675, 2444141, 2444221, 2447418, 2441658, 2442664, 3266899, 2473221, 2445496, 5221394, 2443339, 4553469) AND countrycode = 'BE' AND "year" &gt;= 1900 AND hasCoordinate = TRUE AND genusKey IS NOT NULL AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE') AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE') AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID') AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH') AND (LOWER(identificationVerificationStatus) NOT IN ( 'unverified', 'unvalidated', 'not validated', 'under validation', 'not able to validate', 'control could not be conclusive due to insufficient knowledge', 'uncertain', 'unconfirmed', 'unconfirmed - not reviewed', 'validation requested' ) OR identificationVerificationStatus IS NULL) AND COALESCE(coordinateUncertaintyInMeters, 1000) &lt;= 10000 GROUP BY "year", eeaCellCode, classKey, class, genusKey, genus ORDER BY "year" DESC, eeaCellCode ASC, genusKey ASC;

 The dataset's 109 records were derived from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012080-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17466786
title: PISM model output data from Winkelmann et al. (Nature Climate Change, 2026) publication

description: This dataset contains the PISM model output data of the Antarctic Ice Sheet critical thresholds simulations published and discussed in

Winkelmann, R., Garbe, J., Donges, J. F., and Albrecht, T. Mapping tipping risks from Antarctic ice basins under global warming. Nature Climate Change, in press.

A detailed description of the individual file contents is given in README.txt below. The corresponding PISM model code used for these simulations is archived here.

In case of questions, feel free to contact us at julius.garbe@pik-potsdam.de or ricarda.winkelmann@pik-potsdam.de.
DOI: 10.5281/zenodo.17466785
title: PISM model output data from Winkelmann et al. (Nature Climate Change, 2026) publication

description: This dataset contains the PISM model output data of the Antarctic Ice Sheet critical thresholds simulations published and discussed in

Winkelmann, R., Garbe, J., Donges, J. F., and Albrecht, T. Mapping tipping risks from Antarctic ice basins under global warming. Nature Climate Change, in press.

A detailed description of the individual file contents is given in README.txt below. The corresponding PISM model code used for these simulations is archived here.

In case of questions, feel free to contact us at julius.garbe@pik-potsdam.de or ricarda.winkelmann@pik-potsdam.de.
DOI: 10.17026/ss/4jjtzw
title: Replication Data for: Involuntary resettlement for infrastructural development projects: Redesigning an evaluation framework on impacts on the population in host communities

description: The datasets contain information which was collected for a PhD dissertation on the perceived impacts of involuntary resettlement due to a dam construction on the people in two host communities: The case study of Bui Dam in Ghana. It contains interviews transcripts, focus groups and questionnaires used to evaluate the perceived impacts of site implementation processes of dam-induced involuntary resettlement programmes and their governance on the population in host communities in Bui Dam, Ghana.
DOI: 10.5281/zenodo.18258388
title: Crotalaria tweedieana Benth. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.15468/dl.b434yp
title: Occurrence Download

description: A dataset containing 12379 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is MNW - Small and medium-sized carnivores’ observations in Flanders, Belgium"
 ]
}

 The dataset includes 12379 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012117-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18258387
title: Crotalaria tweedieana Benth. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.5281/zenodo.17652293
title: Dataset for 'Phytoplankton Photophysiology Traces Iron Stress Hotspot in the South Pacific Ocean'

description: Dataset for 'Phytoplankton Photophysiology Traces Iron Stress Hotspot in the South Pacific Ocean' by Yuan et al., 2025
DOI: 10.15468/dl.cfmk3f
title: Occurrence Download

description: A dataset containing 355864 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae",
 "Year 2007-2026"
 ]
}

 The dataset includes 355864 records from 535 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012030-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18258398
title: Croton L. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.5281/zenodo.18258397
title: Croton L. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.34740/kaggle/dsv/14508508
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.4gmex9
title: Occurrence Download

description: A dataset containing 1552 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "OccurrenceStatus is Present",
 "TaxonKey is Tapirus terrestris",
 "Year 1994-2026"
 ]
}

 The dataset includes 1552 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012118-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18258415
title: 14-the-orchard-that-dreamed-of-fire-arabic
DOI: 10.5281/zenodo.18258416
title: 14-the-orchard-that-dreamed-of-fire-arabic
DOI: 10.15468/dl.v2jj3j
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Oxytropis podoloba"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012120-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5258/soton/d3792
title: Surface Water Transitions 1984-2022: A Global Dataset at Annual Resolution

description: This dataset provides a comprehensive global analysis of surface water dynamics, mapping areas where water has advanced or receded and capturing the timing of these transitions at annual resolution. Using Landsat time series data from 1984 to 2022, this dataset tracks long-term changes in rivers, lakes, reservoirs, and other water bodies, offering critical insights into hydrological shifts driven by natural and anthropogenic factors. The dataset is structured to include: Water Transition Data – Raster files indicating areas of water advance and recession, along with the year in which these changes occurred. Statistical Summary (GeoJSON) – A spatial file containing aggregated statistics, including the magnitude and direction of water transitions for specific regions or water bodies. Code (TXT) – The Google Earth Engine (GEE) Javascript used to process Landsat imagery and generate the dataset. This dataset is intended for use by researchers, policymakers, water resource managers, and conservationists seeking to understand water dynamics on a global scale. It can support studies on river meandering, wetland monitoring, floodplain dynamics, and the impacts of climate change on surface water distribution. The Water Transition image consists of two bands: Band 1 (b1) represents water advance, while Band 2 (b2) represents water recession.
DOI: 10.5281/zenodo.18258413
title: Croton aberrans Müll.Arg. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.5281/zenodo.18258414
title: Croton aberrans Müll.Arg. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.5281/zenodo.17361387
title: Replication Package for "Beyond the YAML File: Understanding Real-World GitHub Actions Workflow Adoption"

description: This repository contains the replication package for the study "Beyond the YAML File: Understanding Real-World GitHub Actions Workflow Adoption" . It provides the code, data artifacts, and instructions necessary to reproduce and access the quantitative and qualitative analyses from the paper.

Repository structure

- data-pipelines-and-analysis/  - data_pipeline/: End-to-end data collection, storage, and analysis pipeline.    - collect_data.py: Entry point to collect data from the GitHub API.    - config/: Configuration (API tokens, runtime options).    - crawlers/: Modular crawlers for repositories, commits, pull requests, workflow runs, and jobs.    - database/: DB connection and ORM-like models used during collection.    - persistence/: Storage interfaces and stores.    - data/: Lightweight helpers and logs for local data handling.    - analysis/: Reproduction scripts for figures, tables, and statistics used in the paper. Includes figures/ and intermediate data/ CSVs used by scripts.    - services/ and scripts/: Utilities and checks (e.g., data quality scripts).    - README.md: Detailed setup, configuration, and execution steps for the pipeline and analyses.  - manual_and_qualitative/: CSVs and notes for manual and qualitative analysis. See its README.md for details and suggested usage.

Quick start

Reproducing the pipeline and analysis:

1. Navigate to data-pipelines-and-analysis/data_pipeline/.2. Create and activate a virtual environment.3. Install requirements: pip install -r requirements.txt4. Follow the instructions in data-pipelines-and-analysis/data_pipeline/README.md to configure credentials, run data collection, and execute analysis scripts in analysis/.

For qualitative artifacts and manual coding resources, see data-pipelines-and-analysis/manual_and_qualitative/README.md.

Reproducing figures and tables

The analysis/ folder inside data_pipeline/ contains scripts that generate the figures and summary tables used in the paper. Many scripts read from analysis/data/ and write outputs to analysis/figures/. Refer to each script's docstring and the data_pipeline/README.md.
DOI: 10.5281/zenodo.18258226
title: Replication Package for "Beyond the YAML File: Understanding Real-World GitHub Actions Workflow Adoption"

description: This repository contains the replication package for the study "Beyond the YAML File: Understanding Real-World GitHub Actions Workflow Adoption" . It provides the code, data artifacts, and instructions necessary to reproduce and access the quantitative and qualitative analyses from the paper.

Repository structure

- data-pipelines-and-analysis/  - data_pipeline/: End-to-end data collection, storage, and analysis pipeline.    - collect_data.py: Entry point to collect data from the GitHub API.    - config/: Configuration (API tokens, runtime options).    - crawlers/: Modular crawlers for repositories, commits, pull requests, workflow runs, and jobs.    - database/: DB connection and ORM-like models used during collection.    - persistence/: Storage interfaces and stores.    - data/: Lightweight helpers and logs for local data handling.    - analysis/: Reproduction scripts for figures, tables, and statistics used in the paper. Includes figures/ and intermediate data/ CSVs used by scripts.    - services/ and scripts/: Utilities and checks (e.g., data quality scripts).    - README.md: Detailed setup, configuration, and execution steps for the pipeline and analyses.  - manual_and_qualitative/: CSVs and notes for manual and qualitative analysis. See its README.md for details and suggested usage.

Quick start

Reproducing the pipeline and analysis:

1. Navigate to data-pipelines-and-analysis/data_pipeline/.2. Create and activate a virtual environment.3. Install requirements: pip install -r requirements.txt4. Follow the instructions in data-pipelines-and-analysis/data_pipeline/README.md to configure credentials, run data collection, and execute analysis scripts in analysis/.

For qualitative artifacts and manual coding resources, see data-pipelines-and-analysis/manual_and_qualitative/README.md.

Reproducing figures and tables

The analysis/ folder inside data_pipeline/ contains scripts that generate the figures and summary tables used in the paper. Many scripts read from analysis/data/ and write outputs to analysis/figures/. Refer to each script's docstring and the data_pipeline/README.md.
DOI: 10.15468/dl.rkew95
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Eurya prunifolia"
 ]
}

 The dataset includes 11 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012122-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xxdmwh
title: Occurrence Download

description: A dataset containing 80481 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cardamine impatiens"
 ]
}

 The dataset includes 80481 records from 1068 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012012-260108223611665/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.29177025.v1
title: Additional file 3 of Defining three dimensional chromatin structures of pediatric and adolescent B cells using primary B cell and EBV-immortalized B cell reference genomes

description: Supplementary Material 3.
DOI: 10.6084/m9.figshare.29177055
title: Additional file 2 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 2: Source data related to Figs. 1–2. Sheet “C2 T-CAGE-log2 TPM” site information and TPM values of the m7G sites identified using C2T-APP and CAGE-seq. Sheet “Reads-distribution” the reads coverage distribution of different methods. Sheet “mESC-multi-omics” gene expression level of mESC calculated using cap reads, tail reads, or total reads. Sheet “mESC-Tail-length-dis” tail length distribution of U-tail transcripts or total transcripts.
DOI: 10.6084/m9.figshare.29177055.v1
title: Additional file 2 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 2: Source data related to Figs. 1–2. Sheet “C2 T-CAGE-log2 TPM” site information and TPM values of the m7G sites identified using C2T-APP and CAGE-seq. Sheet “Reads-distribution” the reads coverage distribution of different methods. Sheet “mESC-multi-omics” gene expression level of mESC calculated using cap reads, tail reads, or total reads. Sheet “mESC-Tail-length-dis” tail length distribution of U-tail transcripts or total transcripts.
DOI: 10.6084/m9.figshare.29177058
title: Additional file 3 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 3: Source data related to Fig. 3. Sheet “M3 WT-KO-GV-noGap-matrix” single cell gene reads count matrix of GV oocytes calculated using non-cap reads. Sheet “M3 WT-KO-GV-Gap-matrix” single cell reads count matrix of GV oocytes calculated using cap reads. Sheet “M3 WT-KO-GV-m6 m-matrix” single cell reads count matrix of GV oocytes calculated using m6Am reads. Sheet “M3 WT-KO-metaData” the sample information of scm6A-seq data.
DOI: 10.6084/m9.figshare.29177058.v1
title: Additional file 3 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 3: Source data related to Fig. 3. Sheet “M3 WT-KO-GV-noGap-matrix” single cell gene reads count matrix of GV oocytes calculated using non-cap reads. Sheet “M3 WT-KO-GV-Gap-matrix” single cell reads count matrix of GV oocytes calculated using cap reads. Sheet “M3 WT-KO-GV-m6 m-matrix” single cell reads count matrix of GV oocytes calculated using m6Am reads. Sheet “M3 WT-KO-metaData” the sample information of scm6A-seq data.
DOI: 10.6084/m9.figshare.29177061.v1
title: Additional file 4 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 4: Source data related to Fig. 4. Sheet “GV-MII-CHX-cap” gene expression level of GV, MII, and CHX treated MII calculated using cap reads. Sheet “GV-MII-CHX-genebody” gene expression level of GV, MII, and CHX treated MII calculated using non-cap reads. Sheet “GV-MII-CHX-tail” gene expression level of GV, MII, and CHX treated MII calculated using tail reads.
DOI: 10.6084/m9.figshare.29177061
title: Additional file 4 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 4: Source data related to Fig. 4. Sheet “GV-MII-CHX-cap” gene expression level of GV, MII, and CHX treated MII calculated using cap reads. Sheet “GV-MII-CHX-genebody” gene expression level of GV, MII, and CHX treated MII calculated using non-cap reads. Sheet “GV-MII-CHX-tail” gene expression level of GV, MII, and CHX treated MII calculated using tail reads.
DOI: 10.6084/m9.figshare.29177064
title: Additional file 5 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 5: Source data related to Fig. 5. Sheet “cap” gene reads count of individual human oocytes calculated using cap reads. Sheet “GeneBody” gene reads count of individual human oocytes calculated using non-cap reads. Sheet “polyA” gene reads count of individual human oocytes calculated using polyreads. Sheet “m6 Am” gene reads count of individual human oocytes calculated using m6Am reads. Sheet “m6 A” gene reads count of individual human oocytes calculated using m6A reads. Sheet “TailLength” polylength of each APA sites of individual human oocytes calculated using m6A reads.
DOI: 10.6084/m9.figshare.29177064.v1
title: Additional file 5 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 5: Source data related to Fig. 5. Sheet “cap” gene reads count of individual human oocytes calculated using cap reads. Sheet “GeneBody” gene reads count of individual human oocytes calculated using non-cap reads. Sheet “polyA” gene reads count of individual human oocytes calculated using polyreads. Sheet “m6 Am” gene reads count of individual human oocytes calculated using m6Am reads. Sheet “m6 A” gene reads count of individual human oocytes calculated using m6A reads. Sheet “TailLength” polylength of each APA sites of individual human oocytes calculated using m6A reads.
DOI: 10.6084/m9.figshare.29177067
title: Additional file 6 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 6. A comprehensive result of the polystructure of mESC cell line, the result file is an original output of C2T-APP.
DOI: 10.6084/m9.figshare.29177067.v1
title: Additional file 6 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 6. A comprehensive result of the polystructure of mESC cell line, the result file is an original output of C2T-APP.
DOI: 10.6084/m9.figshare.29177070
title: Additional file 7 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 7. Excel file contains raw individual data pointsfor each figure. Data are organized into separate worksheets, with each sheet corresponding to a specific figure.
DOI: 10.6084/m9.figshare.29177070.v1
title: Additional file 7 of RNA multi-omics in single cells reveal rhythmical RNA reshaping during human and mouse oocyte maturation

description: Additional file 7. Excel file contains raw individual data pointsfor each figure. Data are organized into separate worksheets, with each sheet corresponding to a specific figure.
DOI: 10.6084/m9.figshare.29177079
title: Additional file 1 of Effectiveness of potential attractants to the apple snail Pomacea canaliculata (Caenogastropoda: Ampullariidae)

description: Additional file1 (XLSX 15 KB)
DOI: 10.6084/m9.figshare.29177079.v1
title: Additional file 1 of Effectiveness of potential attractants to the apple snail Pomacea canaliculata (Caenogastropoda: Ampullariidae)

description: Additional file1 (XLSX 15 KB)
DOI: 10.15468/dl.wfp45h
title: Occurrence Download

description: A dataset containing 862 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Lionycteris spurrelli Thomas, 1913"
 ]
}

 The dataset includes 862 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011192-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25935/4tak-5225
title: STEREO/Waves/LFR-HFR L3 DF Dataset

description: This collection is contains the daily direction finding (aka goniopolarimetric) Level 3 datasets for the Waves/LFR and Waves/HFR receivers onboard the STEREO-A and STEREO-B spacecraft.