cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/248c3t93fz.1
title: Exploring Mechanisms of Early Acquired Resistance to Doxorubicin in Melanoma in 3D Model

description: Supplementary data to paper: "Exploring Mechanisms of Early Acquired Resistance to Doxorubicin in Melanoma in 3D Model" by Negrea et al., 2025. 
These data represent: 1) Supplementary Figure 1. GSEA Enrichment plots; 2) Supplementary Table 1. RT-qPCR Primers sequences; 3) Supplementary Figure 2. RT-qPCR results; 4) Supplementary Table 2. All DEGs; 5) Supplementary Table 3.1 GO and and 3.2. KEGG analysis results; 6) Supplementary Table 4. GSEA analysis; 7) Supplementary Table_5_DEG in selected processes;
DOI: 10.24381/cds.6860a573
title: ERA5 monthly averaged data on pressure levels from 1940 to present
DOI: 10.26021/canterburynz.28700828.v1
title: Supporting data for "Incorporating science communication and bicultural knowledge in teaching a blended volcanology course"

description: This data is the data used to support the manuscript titled Incorporating science communication and bicultural knowledge in teaching a blended volcanology course, which is to be published in Geoscience Communication.
DOI: 10.26066/rds.20828
title: Land cover of Nepal 1990

description: The land cover data for the years 1990 have been derived from Landsat TM 30m images using object based image analysis. The study estimated that 45.15% of Nepal is covered by forests and 25.41% by agriculture.
DOI: 10.3334/cdiac/00001_v2010
title: Global, Regional, and National Fossil-Fuel CO2 Emissions
DOI: 10.34740/kaggle/ds/4464018
title: Brazilian Portuguese Narrative Essays Dataset
DOI: 10.5066/p939ixcp
title: Thresholded abundance models for three invasive plant species in the United States

description: We developed habitat suitability models for three invasive plant species: stiltgrass (Microstegium vimineum), sericea lespedeza (Lespedeza cuneata), and privet (Ligustrum sinense). We applied the modeling workflow developed in Young et al. 2020, developing similar models for occurrence data, but also models trained using species locations with percent cover ≥10%, ≥25%, and ≥50%. We chose predictors from a national library of environmental variables known to physiologically limit plant distributions (Engelstad et al. 2022 Table S1) and relied on human input based on natural history knowledge to further narrow the variable set for each species before developing habitat suitability models. We developed models using five algorithms with VisTrails: Software for Assisted Habitat Modeling [SAHM 2.1.2]. We selected background samples using the target background approach, and took an alternative approach to construct model ensembles by combining first percentile and ten percentile threshold rules (suitability values associated with the lowest one percent and lowest ten percent of the training data) to categorize the continuous output from each algorithm into low (below the one percentile), moderate (between the one and ten percentile), and high (above the ten percentile) suitability. Finally, we summed these to create an ensemble. This data bundle contains the merged data sets used to create the models, the composite raster files for each abundance threshold associated with each species, tabular summaries by management unit (including each species/ composite type combination), and the occurrence points with their associated cover. The spatial data are organized in a separate folder for each species, each containing 5 rasters describing potential habitat suitability for the species at the different abundance thresholds. Each of the rasters represent the composite map (composite_abundX.tif) for each abundance threshold. The bundle documentation files are: 1) 'thresholded_abundance_project_metdata.xml' (this file) which contains the project-level metadata 2) 'mergedDataset.csv' contains the merged data set used to create the models, including location and associated environmental data, for all three species for each thresholded abundance. 3) XX.tif where XX is the raster type explained above (abundance threshold). 4) managementSummary.csv is the tabular summaries by management unit.
DOI: 10.5066/p9j6quf6
title: North American Breeding Bird Survey Dataset 1966 - 2019, version 2019.0

description: The 1966-2018 North American Breeding Bird Survey (BBS) dataset contains avian point count data for more than 700 North American bird taxa (species, races, and unidentified species groupings). These data are collected annually during the breeding season, primarily in June, along thousands of randomly established roadside survey routes in the United States and Canada. Routes are roughly 24.5 miles (39.2 km) long with counting locations placed at approximately half-mile (800-m) intervals, for a total of 50 stops. At each stop, a citizen scientist highly skilled in avian identification conducts a 3-minute point count, recording every bird seen or heard within a quarter-mile (400-m) radius. Surveys begin 30 minutes before local sunrise and take approximately 5 hours to complete. Routes are sampled once per year, with the total number of routes sampled per year growing over time; just over 500 routes were sampled in 1966, while in recent decades approximately 3000 routes have been sampled annually. In addition to avian count data, this dataset also contains survey date, survey start and end times, start and end weather conditions, a unique observer identification number, route identification information, and route location information including country, state, and BCR, as well as geographic coordinates of route start point, and an indicator of run data quality.
DOI: 10.5067/gpm/imergdf/day/07
title: GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 degree V07
DOI: 10.5067/w9foywh0eqz3
title: Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data, Version 1
DOI: 10.5281/zenodo.10570581
title: Data for water activity for Terra Sirenum salt combinations

description: Water activity values for various salt combinations based on Terra Sirenum mineralogy.
DOI: 10.5281/zenodo.10803197
title: Detailed Occurrence of Feather Features in Quartz in Experimentally Shocked Granite

description: Data supporting Figures 1, 3-6 in the main text are available.
description: This research was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI grants JP19H00726, JP21K20383, JP21H01140, and JP21K18660. T.T. and K.K. are supported by a Fostering Joint International Research grant (B)18KK0092.
DOI: 10.5281/zenodo.10845093
title: Data release accompanying JGR publication "Electron-induced radiolysis of water ice and the buildup of oxygen" by Tinner et al.
DOI: 10.5281/zenodo.11514827
title: Melosh model of Acoustic Fluidisation, input files

description: Input files for companion papers submitted to JGR: Planets

1) Hay et al., 2024. "Complex crater collapse: A comparison of the Block and Melosh Acoustic Fluidization Models of transient target weakening".

2) Rajšić et al., 2024. "Using the Melosh model of Acoustic fluidization to simulate impact crater collapse on the Earth and Moon".
DOI: 10.5281/zenodo.12572878
title: Supplementary Dataset for "Grain Size Measurements of the Eolian Stimson Formation, Gale Crater, Mars and Implications for Sand Provenance and Paleoatmospheric Conditions"

description: Grain size measurements and results in support of "Grain Size Measurements of the Eolian Stimson Formation, Gale Crater, Mars and Implications for Sand Provenance and Paleoatmospheric Conditions".

The subfolder "MAHLI images" consists of images taken by the Mars Science Laboratory Curiosity Mars Hand Lens Imager; these images are accesible via the MSL Analyst's Notebook at an.rsl.wustl.edu.

The subfolder "ImageJ ROIs" contains .zip files that can be opened with the ImageJ software, available at imagej.nih.gov/ij.

The subfolder "GRADISTAT results" contains PDFs with grain size statistics that were created from the data in "Grain size measurements" using the GRADISTAT software, available at https://doi.org/10.1002/esp.261.
DOI: 10.5281/zenodo.13352680
title: Spherical Harmonic Coefficients from the SVM by Tsunakawa

description: Spherical harmonic coefficients from the surface vector mapping (SVM) by Tsunakawa et al. (2015) in JGR-Planet
DOI: 10.5281/zenodo.13900820
title: raw crater counts for background regions & python code

description: JMARS .jlf shape files that contain the measurement area polygon and crater measurements (diameters, center lat/lon, and a degradation classification). And .csv files of crater measurements. Names of files indicate the region for the counts. See associated publication for descriptions of those regions.
DOI: 10.5281/zenodo.14534651
title: Data for 'Learning predictable and informative dynamical drivers of extreme precipitation using variational autoencoders'

description: Data necessary to reproduce the results presented in 'Learning predictable and informative dynamical drivers of extreme precipitation using variational autoencoders', submitted to Weather and Climate Dynamics
DOI: 10.5281/zenodo.14756355
title: Fecal microbiota composition analysis in CDKL5 deficiency disorder mouse models

description: In this study, male CDKL5-/y (CDKL5 KO) mice and their male CDKL5+/y WT littermates were investigated.

The composition of the fecal microbiota of CDKL5 KO and WT mice was analysed at different ages. Fresh feces were collected longitudinally from the same subjects at (postnatal day) P25, P32 and P70.

We conducted our analysis on two different CDKL5 null mouse lines born and raised in two distinct animal facilities: the vivarium at the National Research Council in Pisa, Italy (Ref. Amendola et al., 2014 PMID: 24838000), and the vivarium at the Max Planck Institute for Molecular Genetics in Berlin, Germany.

Bacterial DNA was extracted using the QIAamp Powerfecal DNA kit (Qiagen, Cat. no. 12830-50), and its concentration was quantified by the Nanodrop 2000 C Spectrophotometer (ThermoFisher Scientific). 

The 16S rRNA sequencing and analysis was performed by a service offered by Institute of Applied Genomics (IGA, Udine, Italy).  

Library preparation and sequencing. Libraries were prepared by following Illumina 16S Metagenomic Sequencing Library Preparation protocol in two amplification steps: an initial 35 cycle PCR amplification using locus-specific PCR primers and a subsequent amplification that integrates relevant flow-cell binding domains and unique indices (NexteraXT Index Kit, Illumina, FC‐131‐ 1001/FC‐131‐1002).

Primer sequences used for amplification:

16S F (341F) 5’- CCTACGGGNGGCWGCAG -3’

16S R (805R) 5’- GGACTACHVGGGTATCTAATCC -3’

Libraries were sequenced on a MiSeq instrument (Illumina) in paired end 300-bp mode read length. 

We provide the raw data obtained through the 16S rRNA-sequencing experiment.

This dataset contains the following files: 242 files \"fastq.gz\": Files containing the raw sequencing data (FASTQ files) of the 16S rRNA gene profiling carried out on DNA extracted from mouse fecal samples collected longitudinally (at postnatal days (P)-25, P32 and P70) in mice originated from two vivaria: Pisa vivarium (A001) and Berlin vivarium (A002).

As sequencing configuration was performed paired-end, each fragment has two raw reads with the first read in forward orientation (R1), and the second read in reverse-complement orientation (R2). Corresponding reads from the R1 and R2 files are collectively a single paired-end read. Adapter sequences masked with MiSeq Reporter, no quality clipping was provided.

File Naming Convention (Example):

ID2381-2-P25-WT2-A001-B01_S18_L001_R1_001.fastq.gz

Explanation of the symbol in the file name:



ID2381 = Sequencing ID

2 = Serial number identifying each sequenced fragment (each fragment has two files: R1 & R2)

P25 = Postnatal day at collection (P25, P32, or P70- in this case P25)

WT2 = Genotype and individual mouse ID (WT = wild-type, KO = knockout, followed by mouse ID number)

A001 = Vivarium ID (A001 = Pisa, A002 = Berlin)

B01 = Sample batch identifier

S18_L001 = Sequencing-specific information

R1 = Read direction (R1 = forward, R2 = reverse)
DOI: 10.5281/zenodo.14827591
title: Code and data to "Statistical learning and topkriging improve spatio-temporal low-flow estimation"

description: This data and software supports the manuscript "Statistical learning and topkriging improve spatio-temporal low-flow estimation" (https:://doi.org/10.1029/2024WR038329).

The dataset consists of:



all produced predictions of the models (data/predictions.RDS and data/predictions_csv/*)

observational data (data/observations.csv)

additional catchment data (data/catchment_data.csv) used for presenting the figures

state boundaries of Austria as a shape file (data/boundaries.*)

partial predictions of a model-based boosting approach (data/partial_predictions.csv)

Example output of number of EOF, due to long computational time (data/number_eofs.RDS)

IDs of near natural catchments (data/ids_low_flow.csv)


Additionally, the code is provided to:



Compute the number of EOFs (functions/number_eofs.R)

Produce all the figures and tables in the paper (scripts/plotting_results.R)
DOI: 10.5281/zenodo.7652912
title: Results of the crowd-mapping action within the project TeRRIFICA [Dataset No. 2 dated 2023-01-19]

description: The dataset includes the results of the crowd-mapping action within the project "Territorial RRI fostering innovative climate action" - TeRRIFICA (Horizon 2020 under GA 824489) dated 2023-01-19. The data are points added to the map by the users (volunteers) and represent locations where climate change-related issues occur regarding air temperature, air quality, water, soil, and wind (SPOTS). The second part of the dataset is related to the crowd-mapping users and their anonymized characteristics (USERS). More details are available at https://terrifica.eu/.
description: Results of the project TeRRIFICA - Territorial RRI fostering innovative climate action. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 824489.
DOI: 10.5281/zenodo.7670652
title: A hybrid 100-m global land cover dataset with Local Climate Zones for WRF

description: This hybrid 100-m CGLC-MODIS-LCZ global land cover dataset is produced for the Weather Research and Forecasting (WRF) model starting from version 4.5. It is based on 1) the Copernicus Global Land Service Land Cover (CGLC, Buchhorn et al., 2021) product resampled to MODIS IGBP classes (CGLC-MODIS), and 2) the global map of Local Climate Zones (LCZ, Demuzere et al., 2022a, b) that describes the urban and built-up land surface. Both the CGLC and LCZ products are available at a 100-m spatial resolution, are representative for the year 2018, and cover -180°W to 180°E and -60°S to 78°N. Remaining areas are filled with the MODIS land cover classes. This dataset has been implemented into the WRF Preprocessing System (WPS) as tiled binary data files with a new GEOGRID table entry to allow WRF/WPS users to flexibly use this dataset in their studies particularly for urban modeling applications. To display the dataset in QGIS, <em>cmap_Qgis_CGLC_MOD_LCZ.txt </em>can be used as a color scheme. For more details, please read the technical documentation: https://doi.org/10.5281/zenodo.7670792.<br> <br> References: <em>Buchhorn, M., Smets, B., Bertels, L., De Roo, B., Lesiv, M., Tsendbazar, N.-E., Li, L., Tarko, A. Copernicus Global Land Service: Land Cover 100m: version 3 Globe 2015-2019: Product User Manual (Dataset v3.0, doc issue 3.4). Product User Manual; Zenodo, Geneve, Switzerland, September 2020; doi: 10.5281/zenodo.3938963<br> <br> Demuzere M, Kittner J, Martilli A, et al. A global map of local climate zones to support earth system modelling and urban-scale environmental science. Earth Syst Sci Data. 2022a;14(8):3835-3873. doi:10.5194/essd-14-3835-2022</em> <em>Demuzere M, Kittner J, Martilli A, et al. (2022). Global map of Local Climate Zones (2.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6364593</em>
DOI: 10.5281/zenodo.8180677
title: Ebbert Lab Nanopore PCS111 brain cDNA discovery (12 samples - AD vs Controls)

description: For more information about this data see the publication: https://doi.org/10.1038/s41587-024-02245-9

The publication GitHub is a good source of information: https://github.com/UK-SBCoA-EbbertLab/brain_cDNA_discovery

There are also README files in the data that provide more information about what is contained in each directory.

 

Basic information about main directory structure and files:

reproducing_RNA_figures - Contains all references/annotations necessary for reproducing the stats, analysis, and figures for the RNA isoform analysis in the article.

reproducing_nextflow_pipeline - Contains all references/annotations necessary for reproducing the NextFlow pipeline.

proteomics - Fasta reference files files used for proteomics analysis with FragPipe and results output by FragPipe.

transcriptomic_analysis_output - Contains output from transcriptomic analysis including: quality control, counts matrices, new RNA isoform annotations, and the Bambu R object.

counts_transcript.txt - Transcript level counts (does not include any intronic reads).
description: This version has fixed proteomics data.
DOI: 10.6084/m9.figshare.25928296
title: Has OA Moved Past a Lingua Franca? [Data]

description: Data in support of the proceedings: Moulaison-Sandy, H., & Shelton, A. (2024). Has OA moved past a lingua franca? [Short paper] In 87<sup>th</sup> Annual Meeting of the Association for Information Science and Technology (ASIST) 2024, Calgary, Canada. <i>Proceedings of the Association for Information Science and Technology.</i>
DOI: 10.6084/m9.figshare.26391526
title: <b>Atomic-level structural responses of Chang'e-5 ilmenite to space weathering</b>

description: Space weathering records provide insights to better understand the formation and evolution of the lunar regolith. Ilmenite has contrasting responses to different space weathering processes. However, atomic-scale structural modification of ilmenite induced by different space weathering processes remains poorly understood. In this study, we investigate the effects of spacing weathering on lunar ilmenite grains returned from Chang’e-5 (CE-5) mission with the combination of transmission electron microscopy and thermodynamic modeling approaches.
DOI: 10.6084/m9.figshare.28408568
title: High-Res Acoustic and Environmental Data to Monitor <i>Bombus dahlbomii</i> Amid Invasive Species, Habitat Loss

description: Annotated dataset of bee buzzes from Puerto Blest. Bombus dahlbomii and bombus terrestris were present during field recordings.
DOI: 10.7302/pf4m-vn04
title: Y-90 PET/CT & SPECT/CT and Corresponding Contours Dataset 31JULY2020

description: Interest in quantitative imaging of Y-90 is growing because transarterial radioembolization (RE) with Y-90 loaded microspheres is a promising and minimally invasive treatment that is FDA approved for unresectable primary and metastatic liver tumors. These cancers are a leading cause of cancer mortality and morbidity. Radioembolization is a therapy that irradiates liver tumors with radioactive microspheres administered through a microcatheter placed in the hepatic arterial vasculature. Radioembolization is based on the principle that healthy liver and tumor are mainly vascularized by the portal vein and the hepatic artery respectively. As a result, radioactive microspheres are preferentially located in the lesions after they are administered via the hepatic artery.
description: PET/CT (SPECT/CT) images were acquired with Siemens PET/CT (SPECT/CT) system and tumor/organ boundaries have been manually labeled on CT by a radiologist for Y-90 patients in our clinics. All patient private information is anonymized using commercial software.
DOI: 10.11583/dtu.28531154
title: NEB and band structure calculations for APbI<sub>3</sub> (A=Cs, Rb, K) perovskite memristive devices

description: This database contains the input and output files related to the publication: "Engineering of A-Site Cations in APbI₃ (A = Cs, Rb, K) Perovskites for Resistive Switching Control and Self-Rectifying Memristors for Next-Generation Computing Applications"Using Density Functional Theory (DFT) and the VASP software, structural relaxations using the PBEsol functional and spin orbit coupling correction are performed on APbI₃ (A = Cs, Rb, K) perovskites. The band structure is calculated using the HSE06 functional to obtain accurate bandgaps. To investigate the migration barrier of vacancy-assisted I-hopping and A-hopping, climbing image nudged elastic band calculations are performed. This database contains the input files (INCAR, POSCAR, POTCAR and KPOINTS) to reproduce the results of this studies. Output files (CONTCAR, OUTCAR) are also present, showing the results obtained.
DOI: 10.13026/4jqj-jw95
title: MIMIC-CXR Database

description: The MIMIC Chest X-ray (MIMIC-CXR) Database v2.0.0 is a large publicly
available dataset of chest radiographs in DICOM format with free-text
radiology reports. The dataset contains 377,110 images corresponding to
227,835 radiographic studies performed at the Beth Israel Deaconess Medical
Center in Boston, MA. The dataset is de-identified to satisfy the US Health
Insurance Portability and Accountability Act of 1996 (HIPAA) Safe Harbor
requirements. Protected health information (PHI) has been removed. The dataset
is intended to support a wide body of research in medicine including image
understanding, natural language processing, and decision support.
DOI: 10.13026/kp08-ws25
title: CheXchoNet: A Chest Radiograph Dataset with Gold Standard Echocardiography Labels

description: Existing chest radiograph datasets, such as CheXpert and ChestX-ray14, have
driven the development of new machine learning approaches to achieve expert or
near-expert level performance on a variety of tasks. The primary focus of
models developed using these datasets has been to replicate human-level
performance by training on labels computationally extracted from radiology
reports. We propose a different paradigm: pair an existing diagnostic test
with labels from a more accurate, higher fidelity diagnostic test. This
approach seeks to ask whether data from a cheaper, lower fidelity diagnostic
test contains information for detection of pathologies using more accurate,
gold standard labels. In the context of chest X-rays, a good example is the
radiologic comment of cardiomegaly, a catch-all term or an abnormally enlarged
heart. Cardiomegaly is known to be poorly predictive of cardiac disease and
does not trigger meaningful clinical action. Instead, we can pair chest X-rays
with gold standard structural heart disease labels derived from
echocardiograms conducted on the same patients. This resource contains 71,589
unique chest X-rays from 24,689 different patients paired with key
echocardiography measurements indicative of left ventricular hypertrophy and
dilated left ventricle, pathologies which occur during early stage heart
failure. The data also includes information about the relative times of the
chest X-rays, the age/sex of the patient at the time of recording, and related
metadata information. This data can be used as a resource for the community to
build novel approaches to detect clinically actionable labels.
DOI: 10.17189/1519460
title: MOLA MISSION EXPERIMENT GRIDDED DATA RECORD
DOI: 10.17189/1519470
title: MRO CRISM MAP-PROJECTED TARGETED REDUCED DATA RECORD V1.0
DOI: 10.17189/1519494
title: MSL MARS CHEMCAM REMOTE MICRO-IMAGER CAMERA 5 RDR V1.0
DOI: 10.17189/1520169
title: MSL MARS HAND LENS IMAGER 4 RDR ZSTACK V1.0
DOI: 10.17189/1520213
title: ODYSSEY THEMIS IR GEO V2.0
DOI: 10.17189/1520227
title: MRO MARS HIGH RESOLUTION IMAGING SCIENCE EXPERIMENT DTM V1.0
DOI: 10.17189/1520250
title: LRO MOON LROC 2 EDR V1.0
DOI: 10.17189/1520266
title: MRO CONTEXT CAMERA EXPERIMENT DATA RECORD LEVEL 0 V1.0
DOI: 10.17189/1520396
title: MSL MARS HAND LENS IMAGER 2 EDR ZSTACK V1.0