cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15625961
title: Okyeame: Full Contents of the Ghanaian Literary Magazine 1961-1972

description: Okyeame [Ɔkyeame] was a literary magazine published in Ghana which appeared in eight issues between January 1961 and November 1972. The magazine featured poetry, fiction, drama and cultural commentary, as well as art work. It was published by the Ghana Society of Writers and the Ghana Writers’ Workshop, in association with the Institute of African Studies, University of Ghana, Legon, and with support variously from the Arts Council of Ghana and the Institute of Art and Culture. It was overseen by an editorial committee, and many issues were edited by Efua Sutherland.

The dataset was compiled mainly from print copies held at the School of African and Oriental Studies, University of London, with additional materials from materials from Cornell University Library and the Balme Library at the University of Ghana, Legon.
DOI: 10.15468/dl.vr3eu2
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Psittacanthus palmeri (S.Watson) Barlow & Wiens",
 "Year 2020-2025"
 ]
}

 The dataset includes 11 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031232-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a2dccw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Arthroleptella villiersi Hewitt, 1935",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((20.7576 -24.3688,20.529 -24.0715,20.509 -24.0715,20.509 -28.5786,25.5395 -28.5786,25.5395 -24.0715,25.1306 -24.0715,24.9333 -24.4571,23.8962 -24.2467,22.8065 -24.295,22.3719 -24.7207,22.2323 -25.547,22.0387 -25.7188,21.7833 -25.7784,21.5388 -25.7113,21.3553 -25.5415,20.7576 -24.3688))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031233-250525065834625/datasets/export for details.
DOI: 10.15468/dl.szvaq2
title: Occurrence Download

description: A dataset containing 7724 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Australia",
 "TaxonKey is Bubalus bubalis (Linnaeus, 1758)"
 ]
}

 The dataset includes 7724 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031234-250525065834625/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.29271185
title: Supplementary material of the paper investigating students' perception of using POGIL in teaching Python

description: Supplementary material of the paper investigating students' perception of using POGIL in teaching Python.
DOI: 10.6084/m9.figshare.29271185.v1
title: Supplementary material of the paper investigating students' perception of using POGIL in teaching Python

description: Supplementary material of the paper investigating students' perception of using POGIL in teaching Python.
DOI: 10.15468/dl.c7qwe4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Arthroleptella villiersi Hewitt, 1935",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((20.529 -24.0715,20.509 -24.0455,20.509 -24.0715,20.529 -24.0715))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031235-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.29260109
title: <b>PUBLISHED GROUP 2 DESIGN AND IMPLEMENTATION OF INTERACTIVE DATA VISUALIZATION FOR WEB APPLICATIONS. IT IS THE DESIGN AND IMPLEMENTATION OF INTERACTIVE DATA VISUALIZATION FOR WEB APPLICATION. IT ALSO INCLUDE A FULL WRITE-UP REPORT. </b>

description: Interactive location finder data visualization for our unique web app called GeoPulse Navigator.
DOI: 10.6084/m9.figshare.29260109.v1
title: <b>PUBLISHED GROUP 2 DESIGN AND IMPLEMENTATION OF INTERACTIVE DATA VISUALIZATION FOR WEB APPLICATIONS. IT IS THE DESIGN AND IMPLEMENTATION OF INTERACTIVE DATA VISUALIZATION FOR WEB APPLICATION. IT ALSO INCLUDE A FULL WRITE-UP REPORT. </b>

description: Interactive location finder data visualization for our unique web app called GeoPulse Navigator.
DOI: 10.25921/t8w4-bb79
title: NESDIS Level 3 Blended Enterprise Rainfall Rates (ENTRAIN)
DOI: 10.5281/zenodo.15626074
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250609r Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250609r Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.5281/zenodo.15626075
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250609r Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250609r Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.15468/dl.7494sb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Arthroleptella villiersi Hewitt, 1935",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((25.5395 -23.2724,25.1306 -24.0715,25.5395 -24.0715,25.5395 -23.2724))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031236-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.29270873
title: creditcard Dataset

description: <b>Title:</b> Credit Card Transactions Dataset for Fraud Detection (Used in: A Hybrid Anomaly Detection Framework Combining Supervised and Unsupervised Learning)<b>Description:</b>This dataset, commonly known as <i>creditcard.csv</i>, contains anonymized credit card transactions made by European cardholders in September 2013. It includes 284,807 transactions, with 492 labeled as fraudulent. Due to confidentiality constraints, features have been transformed using PCA, except for 'Time' and 'Amount'.This dataset was used in the research article titled <i>"A Hybrid Anomaly Detection Framework Combining Supervised and Unsupervised Learning for Credit Card Fraud Detection"</i>. The study proposes an ensemble model integrating techniques such as Autoencoders, Isolation Forest, Local Outlier Factor, and supervised classifiers including XGBoost and Random Forest, aiming to improve the detection of rare fraudulent patterns while maintaining efficiency and scalability.<b>Key Features:</b>30 numerical input features (V1–V28, Time, Amount)Class label indicating fraud (1) or normal (0)Imbalanced class distribution typical in real-world fraud detection<b>Use Case:</b><br>Ideal for benchmarking and evaluating anomaly detection and classification algorithms in highly imbalanced data scenarios.<b>Source:</b><br>Originally published by the Machine Learning Group at Université Libre de Bruxelles.<br>https://www.kaggle.com/mlg-ulb/creditcardfraud<b>License:</b><br>This dataset is distributed for academic and research purposes only. Please cite the original source when using the dataset.
DOI: 10.6084/m9.figshare.29270873.v1
title: creditcard Dataset

description: <b>Title:</b> Credit Card Transactions Dataset for Fraud Detection (Used in: A Hybrid Anomaly Detection Framework Combining Supervised and Unsupervised Learning)<b>Description:</b>This dataset, commonly known as <i>creditcard.csv</i>, contains anonymized credit card transactions made by European cardholders in September 2013. It includes 284,807 transactions, with 492 labeled as fraudulent. Due to confidentiality constraints, features have been transformed using PCA, except for 'Time' and 'Amount'.This dataset was used in the research article titled <i>"A Hybrid Anomaly Detection Framework Combining Supervised and Unsupervised Learning for Credit Card Fraud Detection"</i>. The study proposes an ensemble model integrating techniques such as Autoencoders, Isolation Forest, Local Outlier Factor, and supervised classifiers including XGBoost and Random Forest, aiming to improve the detection of rare fraudulent patterns while maintaining efficiency and scalability.<b>Key Features:</b>30 numerical input features (V1–V28, Time, Amount)Class label indicating fraud (1) or normal (0)Imbalanced class distribution typical in real-world fraud detection<b>Use Case:</b><br>Ideal for benchmarking and evaluating anomaly detection and classification algorithms in highly imbalanced data scenarios.<b>Source:</b><br>Originally published by the Machine Learning Group at Université Libre de Bruxelles.<br>https://www.kaggle.com/mlg-ulb/creditcardfraud<b>License:</b><br>This dataset is distributed for academic and research purposes only. Please cite the original source when using the dataset.
DOI: 10.15468/dl.xtz2mv
title: Occurrence Download

description: A dataset containing 212 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Arthroleptella villiersi Hewitt, 1935",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((20.2855 -34.7533,20.509 -34.5676,20.509 -32.9007,17.7723 -32.9007,17.8156 -33.0786,18.3471 -33.7176,18.3748 -33.8287,18.2181 -34.0492,18.3197 -34.3408,18.4452 -34.429,18.5435 -34.4213,18.5872 -34.3667,18.5363 -34.167,18.7345 -34.1508,18.7216 -34.3637,18.7808 -34.4521,19.0289 -34.4206,19.0831 -34.4835,19.2655 -34.5017,19.2032 -34.6157,19.2394 -34.6926,19.375 -34.6963,19.6091 -34.8524,19.8251 -34.8396,19.9798 -34.9064,20.1081 -34.8731,20.1517 -34.7847,20.2855 -34.7533))"
 ]
}

 The dataset includes 212 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031237-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15626017
title: Seasonal variability in velocity of a Himalayan Glacier driven by subglacial hydrology: Modeling scripts and data

description: Description of Files Contained in this Repository

 

Contact: Aleah Sommers

aleah.n.sommers@dartmouth.edu

 

Please note that these scripts and model output are in the format of the Ice-sheet and Sea-level System Model (ISSM). For handling, you can download and install ISSM pre-compiled binaries from this website: issm.jpl.nasa.gov/download/

 

Matlab scripts to run ISSM/SHAKTI:





runme_HMA_DD_clean.m – Set up model domain, run initial SHAKTI simulation




runme_HMA_continue_SHAKTI.m – Continue SHAKTI simulation from end of a previous simulation, or turn on coupling to velocity and continue




runme_HMA_continue_seasonal_MOLHO_clean.m – Beginning from end of winter coupled simulation, run a seasonal simulation



 

Supporting data:





DD.exp – Outline of model domain




DD_DEM.mat – Surface elevation (from LEGOS and OMP, 2025)




DD_thickness.mat – Ice thickness (from Millan et al., 2022)



 

Model output:





DD_1to2yr.mat – SHAKTI subglacial hydrology spin-up simulation with zero velocity and zero meltwater inputs




DD_coupled_1yr_paper.mat – SHAKTI-ISSM coupled winter spin-up simulation




DD_seasonal_paper.mat – SHAKTI-ISSM model output for seasonal coupled simulation



 

Plotting scripts:





plot_DD_timeseries_ZoneAB.m




plot_DD_seasonal_spatial.m




plot_DD_SI_figs.m



 

Animation:





movie_DD_seasonal_normal5x.mp4 – Animation of seasonal simulation showing change in velocity (left panel; m per year) and change in effective pressure (right panel; Pa), relative to winter.
DOI: 10.15468/dl.tjkzex
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Arthroleptella villiersi Hewitt, 1935",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((35.628 -23.023,35.6007 -22.9702,35.6007 -23.165,35.628 -23.023))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031238-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.15626103
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250609r Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250609r Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.5281/zenodo.15626104
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250609r Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250609r Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.15468/dl.gxzfux
title: Occurrence Download

description: A dataset containing 5600 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "OccurrenceStatus is Present",
 "TaxonKey is Notropis boops Gilbert, 1884"
 ]
}

 The dataset includes 5600 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031239-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10408588
title: JUMP CRISPR (+anti)correlated cosine similarities
DOI: 10.5281/zenodo.10416695
title: JUMP CRISPR (+anti)correlated cosine similarities
DOI: 10.5281/zenodo.10453141
title: JUMP CRISPR (+anti)correlated cosine similarities
DOI: 10.5281/zenodo.10453167
title: JUMP CRISPR (+anti)correlated cosine similarities
DOI: 10.5281/zenodo.10457424
title: JUMP CRISPR (+anti)correlated cosine similarities
DOI: 10.5281/zenodo.10457432
title: JUMP CRISPR (+anti)correlated cosine similarities
DOI: 10.5281/zenodo.10535986
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10542737
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10551880
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10551990
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10552035
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10552553
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10552568
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10565127
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10573667
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10689988
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10823556
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.10823586
title: JUMP CRISPR and ORF (+anti)correlated cosine distances
DOI: 10.5281/zenodo.11188477
title: JUMP Exploration databases
DOI: 10.5281/zenodo.12752549
title: JUMP Exploration databases
DOI: 10.5281/zenodo.12766577
title: JUMP Exploration databases
DOI: 10.5281/zenodo.13259495
title: Processed JUMP Datasets: For Web and programmatic exploration.

description: This dataset provides multiple tables for JUMP exploration:- Full datasets contain precomputed analysis: - significance - is the phenotypic activity of a given value (see broad.io/crispr_feature for a formal definition), while distance contains the cosine distance of all perturbations vs all other perturbations within a given dataset.- The features and matches files contain a selection of the raw precomputed analyses and are intended for consumption on a web browser through the Datasette tool (see broad.io/jump-explore for details).

- Lastly, galleries are for quick visualization of the images with all channels collapsed into one (these may be temporarily absent in the latest version of the dataset, you can find them in the previous ones).
DOI: 10.5281/zenodo.14046034
title: Processed JUMP Datasets: For Web and programmatic exploration.

description: This dataset provides multiple precomputed analysis tables to make JUMP data exploration accessible:

- 'X_features.parquet' contains a ranking of the features that distinguish a given perturbation from negative controls.- 'X_gallery.parquet' is for visualization of the images with all channels collapsed into one.- 'X_cosinesim...parquet' contains the pairwise cosine similarity of all perturbations within a given dataset (i.e., orf, crispr). This allows searching for the closest matches for each perturbation of interest or looking at all relationships in a heatmap.- 'X...significance...parquet' is the statistical significance for the phenotypic activity of a given sample (see broad.io/crispr_feature for a formal definition). It shows which perturbations yielded a phenotype distinguishable from negative controls.- 'full' tables contain all the data points from the resulting analysis. Their non-full counterpart contains a subset comprised of the most significant entries, meant for in-browser consumption and queries. - Many of the above tables can be interactively viewed using [JUMPrr tools](https://github.com/broadinstitute/monorepo/tree/main/libs/jump_rr#quick-data-access)
DOI: 10.5281/zenodo.14642108
title: Processed JUMP Datasets: For Web and programmatic exploration.

description: This dataset provides multiple tables for JUMP exploration:- Full datasets contain precomputed analysis: - significance - is the phenotypic activity of a given value (see broad.io/crispr_feature for a formal definition), while distance contains the cosine distance of all perturbations vs all other perturbations within a given dataset.- The features and matches files contain a selection of the raw precomputed analyses and are intended for consumption on a web browser through the Datasette tool (see https://github.com/broadinstitute/monorepo/tree/main/libs/jump_rr#quick-data-access for details).- Lastly, galleries are for quick visualization of the images with all channels collapsed into one.
DOI: 10.5281/zenodo.14648922
title: Processed JUMP Datasets: For Web and programmatic exploration.

description: This dataset provides multiple tables for JUMP exploration:- Full datasets contain precomputed analysis: - significance - is the phenotypic activity of a given value (see broad.io/crispr_feature for a formal definition), while distance contains the cosine distance of all perturbations vs all other perturbations within a given dataset.- The features and matches files contain a selection of the raw precomputed analyses and are intended for consumption on a web browser through the Datasette tool (see https://github.com/broadinstitute/monorepo/tree/main/libs/jump_rr#quick-data-access for details).- Lastly, galleries are for quick visualization of the images with all channels collapsed into one.
DOI: 10.5281/zenodo.14649129
title: Processed JUMP Datasets: For Web and programmatic exploration.

description: This dataset provides multiple tables for JUMP exploration:- Full datasets contain precomputed analysis: - significance - is the phenotypic activity of a given value (see broad.io/crispr_feature for a formal definition), while distance contains the cosine distance of all perturbations vs all other perturbations within a given dataset.- The features and matches files contain a selection of the raw precomputed analyses and are intended for consumption on a web browser through the Datasette tool (see https://github.com/broadinstitute/monorepo/tree/main/libs/jump_rr#quick-data-access for details).- Lastly, galleries are for quick visualization of the images with all channels collapsed into one.
DOI: 10.5281/zenodo.14649162
title: Processed JUMP Datasets: For Web and programmatic exploration.

description: This dataset provides multiple tables for JUMP exploration:- Full datasets contain precomputed analysis: - significance - is the phenotypic activity of a given value (see broad.io/crispr_feature for a formal definition), while distance contains the cosine distance of all perturbations vs all other perturbations within a given dataset.- The features and matches files contain a selection of the raw precomputed analyses and are intended for consumption on a web browser through the Datasette tool (see https://github.com/broadinstitute/monorepo/tree/main/libs/jump_rr#quick-data-access for details).- Lastly, galleries are for quick visualization of the images with all channels collapsed into one.
DOI: 10.5281/zenodo.14649344
title: Processed JUMP Datasets: For Web and programmatic exploration.

description: This dataset provides multiple tables for JUMP exploration:- Full datasets contain precomputed analysis: - significance - is the phenotypic activity of a given value (see broad.io/crispr_feature for a formal definition), while distance contains the cosine distance of all perturbations vs all other perturbations within a given dataset.- The features and matches files contain a selection of the raw precomputed analyses and are intended for consumption on a web browser through the Datasette tool (see https://github.com/broadinstitute/monorepo/tree/main/libs/jump_rr#quick-data-access for details).- Lastly, galleries are for quick visualization of the images with all channels collapsed into one.
DOI: 10.5281/zenodo.14861363
title: Processed JUMP Datasets: For Web and programmatic exploration.

description: This dataset provides multiple tables for JUMP exploration:- Full datasets contain precomputed analysis: - significance - is the phenotypic activity of a given value (see broad.io/crispr_feature for a formal definition), while distance contains the cosine distance of all perturbations vs all other perturbations within a given dataset.- The features and matches files contain a selection of the raw precomputed analyses and are intended for consumption on a web browser through the Datasette tool (see https://github.com/broadinstitute/monorepo/tree/main/libs/jump_rr#quick-data-access for details).- Lastly, galleries are for quick visualization of the images with all channels collapsed into one.