cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.mxzhu2
title: Occurrence Download

description: A dataset containing 1357 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhincodon typus Smith, 1828"
 ]
}

 The dataset includes 1357 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0230703-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vrbens
title: Occurrence Download

description: A dataset containing 172780 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anthyllis vulneraria L., Anticlea elegans (Pursh) Rydb., Antitype suda Geyer, 1832)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 172780 records from 534 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0311182-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w35vgd
title: Occurrence Download

description: A dataset containing 22349 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Puma concolor (Linnaeus, 1771)"
 ]
}

 The dataset includes 22349 records from 355 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0077919-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/7tz4t7cd8c.2
title: Data for "In-Situ Determination of Thermoelastic Properties of Magnesite at High Pressure and Temperature with Implications to Seismic Detectability of Moderately Carbonated Lithologies in the Earth’s Mantle"

description: Experimental data for paper "In-Situ Determination of Thermoelastic Properties of Magnesite at High Pressure and Temperature with Implications to Seismic Detectability of Moderately Carbonated Lithologies in the Earth’s Mantle" by Xu et al., submitted to JGR-Solid Earth for consideration of publication.
DOI: 10.18709/perscido.2022.09.ds376
title: Snow status (wet/dry) in Antarctica from SMMR, SSM/I, AMSR-E and AMSR2 passive microwave radiometers

description: The dataset provides daily binary status (wet/dry) of the snowpack for each pixel at 25 or 12.5 km resolution in Antarctica. This status is retrieved from passive microwave observation at 19 GHz and horizontal polarisation, using an algorithm developed by Torinesi et al. 2013 and Picard and Fily, 2006.


The dataset comprises three timeseries. The longest starts in 1979 and includes observations from SMMR and SSM/I sensors. It has a coarse effective resolution of ~60km and has many data gaps  especially during the SMMR period (<1987). The two other timeseries are from AMSR-E and AMSR2 sensors which features a twice-finer effective resolution, about ~25 km. There are less gaps except in 2011/2012 between AMSR-E and AMSR2.
DOI: 10.25318/3210038401-eng
title: Licensed cannabis production, Census of Agriculture, 2021

description: Census of Agriculture, 2021. Number of licensed cannabis cultivators and production areas under cover or in open fields.
DOI: 10.25422/azu.data.25648626.v1
title: Data and Code for "Reflective Signatures of Unresolved Objects"

description: Data and code for journal paper "Reflective Signatures of Unresolved Objects"
Code folder has two Jupyter Notebooks, one for the simulation/forward model, and one for processing the data.
Data folder contains data presented in the paper and follows the sections of the paper.
<br><br><i>For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu</i>
DOI: 10.35003/mqiygr
title: Replication Data for: Onset of plate motion in the presence of chemical heterogeneities in the mantle and the effect of mantle temperature

description: Various structures observed in Earth’s mantle are considered to have a high density and therefore affect the mantle flow and the plate motion. We analyze the onset time of surface motion for 2D basally heated models with and without dense material. We find that the first motion is delayed for more, deeper or denser chemical heterogeneities. Due to a temperature-dependent viscosity, the temperature difference between the cold surface and a hot mantle leads to a highly viscous surface region. In contrast, in a cold mantle, the temperature difference is too small to form rigid plates. The heat from the core first needs to be transported upwards by plumes. Therefore, it takes longer for highly viscous plates to form. In the period after the Earth’s mantle was (partially) molten, the mantle was hotter than today. Under these conditions, plate motion can occur within approximately the first 0.5 Gyr if no chemical structures are present or if they are initially located at the surface. For a system that additionally has deep chemical heterogeneities, the onset of plate motion will be delayed by at least one order of magnitude. The motion will have been less stable than today, probably showing short subduction events.
DOI: 10.5066/f78s4mzj
title: Collection-1 Landsat OLI Level-2 Surface Reflectance (SR) Science Product

description: Landsat satellite data have been produced, archived, and distributed by the U.S. Geological Survey (USGS) since 1972. Users rely on these data for historical study of land surface change, but shoulder the burden of post-production processing to create applications-ready data sets. In compliance with guidelines established through the Global Climate Observing System, USGS has embarked on production of higher-level Landsat data products to support land surface change studies. Terrestrial variables such as surface reflectance are being prototyped as fundamental input to higher level products such as Burned Area, Fractional Snow Covered Area, and Dynamic Surface Water Extent. These products are intended to provide a framework for producing long-term Landsat science data collections suited for monitoring, assessing, and predicting land surface change over time. \r\n\r\nThe Provisional Landsat 8 Surface Reflectance product is generated from specialized software called L8SR. This algorithm is distinctly different from the algorithm used by USGS to process Landsat 4?5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus Level 1 products to Surface Reflectance, known as the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS).
DOI: 10.5066/f7bk19gz
title: Nutrient and pesticide data collected from the U.S. Geological Survey National Water Quality Network and previous networks, 1980-2015

description: The National Water Quality Network (NWQN) for Rivers and Streams includes 113 surface-water river and stream sites monitored by the U.S. Geological Survey (USGS) National Water Quality Assessment Project. The NWQN includes 23 large river coastal sites, 40 large river inland sites, 30 wadeable stream reference sites, 10 wadeable stream urban sites, and 10 wadeable stream agricultural sites. In addition to the 113 NWQN sites, 3 large inland river monitoring sites from the USGS Cooperative Water Program are also included in this annual water-quality reporting Web site to be consistent with previous USGS studies of nutrient transport in the Mississippi-Atchafalaya River Basin. This data release provides streamflow, nutrient, pesticide and sediment data collected and analyzed by NWQN and other historical water-quality networks from 1980-2015. Data from this release are presented at the USGS Tracking Water Quality page: http://cida.usgs.gov/quality/rivers/home, authored by Deacon, J.R., Lee, C.J., Toccalino, P.L., Warren, M.P., Baker, N.T., Crawford, C.G., Gilliom, R.G., and Woodside, M.D., 2015, Tracking water-quality of the Nation�s rivers and streams, U.S. Geological Survey Web page, http://cida.usgs.gov/quality/rivers, doi:10.5066/F70G3H51
DOI: 10.5066/f7h41pnt
title: eMODIS NDVI

description: Moderate resolution remote sensing provides a means for operational monitoring communities to develop historical trend information and use near real-time deviations from temporal averages to identify areas of change. High quality, consistent and well-calibrated satellite measurements are needed to detect and monitor changes and trends, especially in vegetation patterns useful for drought, crop yield, phenology and fire potential studies. The eMODIS collection is based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired by the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS). Even though MODIS data are beneficial in vegetation studies, there have been usability issues encountered with the reprojection, file format and subsetting. Therefore, eMODIS was developed to specifically address these issues. The eMODIS suite of products includes either 7- or 10-day data composited data sets. Expedited (near real-time) production runs daily for the 7-day continental U.S. products and every five days for the 10-day products in other areas using the last interval of input. There is no expedited production over Alaska. Each data set delivers acquisition, quality and Normalized Difference Vegetation Index (NDVI) information at 250-meter (m) spatial resolution. Because each of the composites are created from a varying number of images, the eMODIS composites include acquisition files to identify which of the possible inputs were used to populate the final composite. The metadata accompanying the data files summarize geographic bounds, projection parameters and product contact information. eMODIS currently produces NDVI and reflectance over the continental U.S., Alaska and Central America/Caribbean and Mexico while Africa and Central Asia production contain NDVI only.
DOI: 10.5066/p9osre0j
title: Radiocarbon Data from Coastal Environments on Montague Island, Alaska

description: This dataset consists of sample descriptions and radiocarbon age data from coastal environments on Montague Island, Alaska, analyzed at the National Ocean Sciences Accelerator Mass Spectrometry Facility.
DOI: 10.5281/zenodo.10056631
title: Data files for thermoelastic properties of Fe3+-rich jeffbenite
DOI: 10.5281/zenodo.10065059
title: Monthly time series of rainfall, potential evapotranspiration and streamflow for 201 catchments in South-East Australia

description: The data set contains data for 201 catchments located in South-Eastern Australia. The data was extracted from the datasets collated by Lerat, Thyer et al. (2020) including rainfall and potential-evapotranspiration data obtained from the Bureau of Meteorology Australian Water Outlook website (Frost, Ramchurn et al. 2016) and streamflow data obtained from the Bureau of Meteorology Water Data Online website (Bureau of Meteorology 2019). The data was collected over the period from 1980 to 2018, split into the two sub-periods 1980-1999 (Period 1) and 1999-2018 (Period 2).
 
Bureau of Meteorology. (2019). "Water Data Online." from http://www.bom.gov.au/waterdata.
Frost, A. J., A. Ramchurn and A. Smith (2016). "The bureau's operational AWRA landscape (AWRA-L) Model." Bureau of Meteorology Technical Report.
Lerat, J., M. Thyer, D. McInerney, D. Kavetski, F. Woldemeskel, C. Pickett-Heaps, D. Shin and P. Feikema (2020). "A robust approach for calibrating a daily rainfall-runoff model to monthly streamflow data." Journal of Hydrology591: 125129.
DOI: 10.5281/zenodo.10407939
title: Supplement to: Evidence for Low-pressure Crustal Anatexis During the Northeast Atlantic Break-up

description: These are the supplementary files for Evidence for Low-pressure Crustal Anatexis During the Northeast Atlantic Break-up, submitted to AGU G-cubed on December 18, 2023. They include (1) a PDF file of all the supplementary figures (S1-S9) and references in the AGU, G-cubed journal format, and (2) an Excel file that includes all supplementary tables (S1-S7).
DOI: 10.5281/zenodo.10779109
title: Supplementary material - Superior Label-free Morpho-Molecular Phenotyping of Living Cancer Cells by Combined Raman Spectroscopy and Phase Tomography

description: The repository features .xls worksheets including all the data measured from three living cancer cell lines (namely, HT29 colon adenoma, RKO colon adenocarcinoma, and T84 lung metastasis of colon adenocarcinoma) used through this work. 



More precisely, we included the following:






In Raman spectra HT29 RKO T84.xls, Raman spectra of HT29s, RKOs and T84s, after standard pre-processing (see Methods, RS data processing and statistics), and their standardized version (Z-score division) used for downstream analysis, namely, PCA and regression; 

In RamanPCA.xls, Raman spectra Principal Component Analysis (PCA) output, including PCA loadings and PCA scores; 

In Phase Tomograms HT29 RKO T84.xls, tomographic tabular data, computed from RI tomograms of HT29s, RKOs and T84s via TomoStudio software (see Methods, TPM data processing and statistics);

In TomographyPCC.xls, PCC matrices of the tomographic tabular data of HT29, RKO and T84, with p-value statistical results;

In Proteins_DM_FitLinear.xls, the raw values of protein peak integral area from Raman spectra and correspondent cell dry mass from phase tomograms of the same cancer cell.
DOI: 10.5281/zenodo.10956296
title: CMIP6 models rarely simulate Antarctic winter sea-ice anomalies as large as observed in 2023

description: Contains processed data to create all figures and tables from the publication Diamond et al. (2024) CMIP6 models rarely simulate Antarctic winter sea-ice anomalies as large as observed in 2023; Geophysical Research Letters [Full reference available on publication]

 

Directory structure and associated contents listed below. Folders contain all data required to make corresponding figure, apart from where indicated. Full description of analysis in Diamond et al. (2024). Unless otherwise indicated, 'SIE' refers to August Antarctic SIE.

 

F1/

f1a_obs_ts.csv: Timeseries of 1979-2023 SIE 

f1b_all_instances.csv: All instances (labelled by model, simulation, and simulation year) where an anomaly of magnitude SIE_2023 was detected. SIE timeseries from years -20 to +20 about each anomaly.

f1b_quartiles.csv: Upper and lower quartiles, mean, and median, computed over all instances.

 

F2/

F2_a.csv: 5--95% range of SIE variability dataset, for all model simulations, and observations.

F2_b.csv: T_aug23, computed using ECDFs, for all model simulations, and multi-model ensemble.

F2_c.csv: T_aug23, computed using GEVs, for all model simulations, and multi-model ensemble.

 

F3/

Data for all figures is already provided elsewhere:

F3a: for observations in SF3/SF3_obs_dataset.csv, and for simulations in SF3/SF3_simulations.csv.

F3b: for multi-model ensemble T_aug23 with associated errors in SF6/SF6_all.csv

F3c: for GEV_estimated T_aug23 for all simulations and models in SF6/SF6_all.csv; and  5--95% ranges of SIE variability datasets in F2/F2_a.csv

 

~

SF1/

SF1_all.csv: SIE timeseries for all model simulations, and associated moving averages.

SF2/

sf2_all.csv: SIE decadal means and ranges for all model simulations.

sf2_quartiles.csv: taken over all simulations above - mean decadal mean in each bin; and lower quartile, median and upper quartile of the decadal ranges in each bin.

SF3/

SF3_obs_dataset.csv: SIE variability dataset for 1979-2023 observations.

SF3_simulations.csv: SIE variability datasets for all model simulations

SF4/

F4_a.csv: p_aug23, computed using ECDFs, for all model simulations, and multi-model ensemble.

F4_b.csv: p_aug22, computed using ECDFs, for all model simulations, and multi-model ensemble.

F4_c.csv: T_aug23, computed using GEVs, for all model simulations, and multi-model ensemble.

F4_d.csv: for all model simulations: p-value that simulation SIE variability dataset is drawn from same probability distribution as observations. Computed using Kolmogorov-Smirnoff 2-sample test.

SF5/

Data for both SF5a and b are already provided in F1/f1b_all_instances.csv.

SF6/

SF6_all.csv: for all model simulations, and multi-model ensemble, p_aug23 and T_aug23, with lower and upper errors (computed from 5--95% confidence interval using bootstrapping)

SF7/

Data for SF7a is already provided elsewhere: for observations in SF3/SF3_obs_dataset.csv, and for simulations in SF3/SF3_simulations.csv.

SF7_all.csv: as for SF6_all.csv, but instead using subset of models.
DOI: 10.5281/zenodo.10967188
title: Capturing alterations of intracellular-extracellular lactate distribution in the brain using diffusion-weighted MR spectroscopy in vivo
DOI: 10.5281/zenodo.10982013
title: Data and Code for "Fault Network Geometry Influences Earthquake Frictional Behavior"

description: This dataset contains the data and code necessary to reproduce the results presented in the paper, "Fault-Network Geometry Influences Earthquake Frictional Behavior" Nature (2024), authored by J. Lee, V. C. Tsai, G. Hirth, A. Chatterjee, and D. T. Trugman.

https://doi.org/10.1038/s41586-024-07518-6
DOI: 10.5281/zenodo.10996329
title: Data and code for: Suppression of nitrogen deposition on global forest soil CH4 uptake depends on nitrogen status

description: Methane (CH4) is the second most important atmospheric greenhouse gas (GHG) and forest soils are a significant sink for atmospheric CH4. Uptake of CH4 by global forest soils is affected by nitrogen (N) deposition; clarifying the effect of N deposition helps to reduce uncertainties of the global CH4 budget. However, it remains an unsolved puzzle why N input stimulates soil CH4 flux (RCH4) in some forests while suppressing it in others. Combining previous findings and data from N addition experiments conducted in global forests, we proposed and tested a “stimulating-suppressing-weakened effect” (“three stages”) hypothesis on the changing responses of RCH4 to N input. Specifically, we calculated the response factors (f) of RCH4 to N input for N-limited and N-saturated forests across biomes; the phased changes in f values supported our hypothesis. We also estimated the global forest soil CH4 uptake budget to be approximately 11.2 Tg yr–1. CH4 uptake hotspots were located predominantly in temperate forests. Furthermore, we quantified that current level of N deposition reduced global forest soil CH4 uptake by ~3%. This suppression effect was more pronounced in temperate forests than in tropical or boreal forests, likely due to differences in N status. The proposed “three stages” hypothesis in this study generalizes the diverse effects of N input on RCH4, which could help improve experimental design. Additionally, our findings imply that by regulating N pollution and reducing N deposition, soil CH4 uptake can be significantly increased in the N-saturated forests in tropical and temperate biomes.

Specifically, Data Set S1 (CH4_exp dataset in main text) was used to derive the response factors of soil CH4 flux to N input in global forests; Data Set S2 (CH4_obs dataset in main text) was used to estimate the soil CH4 fluxes in global forests; Data Sets S3–S7 were used to classify the N-limited and N-saturated forests on global level; Data Set S8 contains environmental factors (MAT, MAP, soil texture, etc.) for global estimations on grid level; Data Set S9 contains global forest soil CH4 budgets reported in previous studies. The data analysis process and produced figures can be replicated with the uploaded R script (Code S1).
DOI: 10.5281/zenodo.11167174
title: Data for "A unified model-based framework for doublet or multiplet detection in single-cell multiomics data"

description: This repository contains all the data necessary for replicating, interpreting, and extending the COMPOSITE multiplet detection results featured in our manuscript, 'A Unified Model-Based Framework for Doublet or Multiplet Detection in Single-Cell Multiomics Data'. The data are ready to be directly used as input for the COMPOSITE cloud-based application or the Python package 'sccomposite' to replicate the results.
DOI: 10.5281/zenodo.4437596
title: Data for "Analysis of metagenome-assembled viral genomes from the human gut reveals diverse putative CrAss-like phages with unique genomic features"

description: Data for "Analysis of metagenome-assembled viral genomes from the human gut reveals diverse putative CrAss-like phages with unique genomic features" (submitted to Nature Communications)
DOI: 10.5281/zenodo.5173012
title: DEVoC

description: Danish Enteric Virome Catalog (DEVoC) with genes, annotations & normalized counts in Danish cohort.
DOI: 10.5281/zenodo.7639053
title: RACMO2.3p3 monthly SMB, SEB and t2m data for Antarctica (1979-2018)

description: This data set includes RACMO2.3p3 (Rp3) data for Antarctica for various model settings at 27 km resolution. Netcdf files are available for the Greenland settings (GRL), fresh snow grain size settings (FSG), fresh dry snow metamorphism experiment (FSM), refreezing grain size experiment (RFG) and the control experiment (CON), including all changes, as is described in the manuscript 'Impact of radiation penetration on Antarctic surface melt and subsurface snow temperatures in RACMO2.3p3'.


Monthly-accumulated (monthlyS) and monthly-averaged (monthlyA) data are available for the surface mass balance (SMB) and 2 m air temperature (t2m) for all experiments and surface energy balance (SEB) for GRL and CON. The data includes the following parameters: snow melt, refreezing, runoff, sublimation (subl), precipitation (precip), surface mass balance (smb), drifting snow erosion (sndiv), sensible heat flux (senf), latent heat flux (latf), shortwave downward radiation (swsd), shortwave upward radiation (swsu), longwave downward radiation (lwsd) and longwave upward radiation (lwsu) / net longwave radiation (lwsn). All output is available between 1979-2018 for GRL and CON; and between 1979-1990 for FSG, FSM and RFG.


UPDATE: Added missing month for all monthlyS variables in the CON data set.
DOI: 10.5281/zenodo.7742183
title: Results from a National Survey of Canadian Perspectives on Predicting River Channel Migration and River Bank Erosion

description: This dataset contains findings from a national survey of Canadian perspectives on predicting river channel migration and river bank erosion. The online survey was conducted by researchers from the University of Guelph from November 2, 2021 through January 31, 2022 and received more than 40 responses from regions across Canada.
description: This research was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) through the Discovery and CGS D programs.