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477
datasets available to search
ShareScore release 0.9.0
Dataset results
477 results for “input data”
Input data for predicted organic carbon content on the Norwegian continental margin
<p>Input data relating to R workflow for predicting organic carbon content on the Norwegian continental margin (https://github.com/diesing-ngu/TOC). The following files are included:</p><p><strong>mosaic_2023-04-21.csv</strong> - Data on organic carbon content in surface sediments from the <a href="https://doi.org/10.5194/essd-15-4105-2023">MOSAIC v2.0</a> database</p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p><p><strong>GrainSizeReg_folk8_classes_2023-06-28.tif</strong> - Georeferenced TIFF-file of predicted substrate classes. Used to update the area of interest (exclude areas mapped as Rock and boulders).</p><p><strong>mud_2023-06-30.tif </strong>- Georeferenced TIFF-file of predicted mud content. Used as an additional predctor.</p>
Input data for predicted mud content on the Norwegian continental margin
<p>Input data relating to R workflow for predicting mud content on the Norwegian continental margin (https://github.com/diesing-ngu/GSMgrids). The following files are included:</p><p><strong>gsm_data.csv</strong> - Data on gravel, sand and mud of surface sediments</p><p><strong>MGObsPkt_150_160_170.shp </strong>- Point shapefile of categorical samples</p><p><strong>predictors_ngb.tif </strong>- Multi-band georeferenced TIFF-file of predictor variables</p><p><strong>predictors_description</strong>.txt - Information on variables stored in predictor_ngb.tif including units, statistics, time period and sources.</p><p><strong>GrainSizeReg_folk8_classes_2023-06-28.tif</strong> - Georeferenced TIFF-file of predicted substrate classes. Used to update the area of interest (exclude areas mapped as Rock and boulders).</p><p><strong>GrainSizeReg_folk8_probabilities_2023-06-28.tif</strong> - Georeferenced TIFF-file of the prediction probabilities of the predicted substrate classes. Used as additional predctors.</p>
Dataset related to article "Polynomial Chaos Expansion of SAR and temperature increase variability in 3 T MRI due to stochastic input data"
<p>Dataset related to simulations described in article:</p> <p>Polynomial Chaos Expansion of SAR and temperature increase variability in 3 T MRI due to stochastic input data. Article citation: Bottauscio et al 2024 <em>Phys. Med. Biol.</em> <a href="https://doi.org/10.1088/1361-6560/ad5070" target="_blank" rel="noopener">https://doi.org/10.1088/1361-6560/ad5070</a></p>
Modelling input data for the case study of the paper "Uncertainty-Based Market-Clearing Models: A Comparative Analysis of the Dutch, French, and German Markets".
<p>This data package includes the modelling input data to replicate the results of the case study included in the paper "Uncertainty-Based Market-Clearing Models: A Comparative<br>Analysis of the Dutch, French, and German Markets". </p> <p>The case study models the Dutch, French and German day-ahead electricity markets, in which the existing capacities of electricity generation and upward- and downward reserve capacities are considered, in addition to 105 wind output realization scenarios for each simulation day. A detailed description of the case study is provided in the readme file.</p> <p>This supplementary data package includes the following files:</p> <p>- Meta Data – Netherlands.xlsx: Dataset containing the meta data for the Dutch case study</p> <p>- Meta Data – France.xlsx: Dataset containing the meta data for the French case study</p> <p>- Meta Data – Germany.xlsx: Dataset containing the meta data for the German case study</p> <p>- Readme.txt: Includes a detailed description of the data packages</p>
The input data of the multi-patch geometries used in: M. Kapl, A. Kosmač, V. Vitrih, Isogeometric collocation for solving the biharmonic equation over planar multi-patch domains, Computer Methods in Applied Mechanics and Engineering 424 (2024) 116882; DOI: 10.1016/j.cma.2024.116882
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MITgcm input data for experiments in Trencham et al. 2024
<p>This dataset includes the input and configuration files for simulations performed using the MITgcm, published in Trencham et al. 2024 (The Impact of Oceanic Feedbacks on Stratosphere-Troposphere Coupling in an Idealised Model). It includes data for fixed-SST experiments (fixed_sst_runs), slab-ocean experiments (slab_ocean_runs), and fully coupled atmosphere-ocean runs (coupled_runs). The latter folder also includes model pickup files corresponding to the last few decades that the control fully coupled simulation was run until, after over 2000 years of model adjustment. The fixed-SST and slab-ocean runs are run from cold using the initial potential temperature and humidity profiles included (theta_cs_a47.bin and q_cs_a47.bin), and take approximately 200 days and 10 years to equilibriate respectively. For further details, see Trencham et al. 2024 and/or contact the corresponding author.</p>
Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands
<p><span>The supporting data for raw data, geographic location of the experimental sites, grid-level maps showing the predicted NCE (%) of global cropland</span></p>
Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands
<p>In-situ observations collected from publications, grid-level maps showing the predicted NCE (%) of global cropland and data-driven model codes</p>
Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands
<p>In-situ observations collected from publications, grid-level maps showing the predicted NCE (%) of global cropland and data-driven model codes</p>
Removal of developmentally regulated microexons has a minimal impact on larval zebrafish brain morphology and function - behavior data input files
<p>Unprocessed (tracking) larval zebrafish behavioral data from mutants with microexons removed. All genes are grouped by their beginning letter, and two runs are included for most mutants.</p>
Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands
<p>Field observation data collected from publications, the references from the main text and data sources , grid-level maps showing prediction of global cultivated land NCE(%) and data-driven model codes </p>
Sample of input data for RASflow
<p>Sample input files for the execution of RASflow, a workflow for RASopathy analysis using the Swift parallel scripting system. (https://github.com/mmondelli/rasflow)</p>
Input data and scripts for "Spatial conservation prioritization for the East Asian islands: a balanced representation of multi-taxon biogeography in a protected area network"
<p>This release contains the input files 'input_data.zip' for the spatial conservation prioritization analysis by Zonation software, which are conducted in Lehtomäki et al. Input data includes biodiversity features (species distribution maps from vascular plants, mammals, birds, reptiles, amphibians, and freshwater fishes), habitat condition map (human influence index), priority mask information (the categorized protected area distribution) and the Japanese prefecture polygons in GeoTiff format, and the list of species attributes for conservation weighting in CSV format. Note that endangered rare species have been excluded from this dataset, though they were reflected in the output files. The Zonation setting files and R scripts for pre- and post analyses are included in 'japan-zsetup-1.0.zip' and also placed at GitHub : https://github.com/cbig/japan-zsetup</p> <p>The output files (priority score maps and removal curves) from the original Zonation analyses are summarized in 'output_from_original.data.zip'</p>
Input files and data for paper "Modules for Experiments in Stellar Astrophysics (MESA): Pulsating Variable Stars, Rotation, Convective Boundaries, and Energy Conservation"
<p>This entry contains input files to reproduce the results of the paper:</p> <p>Modules for Experiments in Stellar Astrophysics (MESA): Pulsating Variable Stars, Rotation, Convective Boundaries, and Energy Conservation.</p> <p>Each zip archive corresponds to a section of the paper, and includes README files in ASCII format with a description. Raw output data and plotting tools are also provided for some of the results.</p>
Data from: Grazing-induced patchiness, not grazing intensity, drives plant diversity in European low-input pastures
<p>Vegetation and soil data from:</p> <p>Tonn, Densing, Gabler, Isselstein: Grazing-induced patchiness, not grazing intensity, drives plant diversity in European low-input pastures, Journal of Applied Ecology</p> <p>The first data sheet contains a description of column names and contents, the second data sheet contains the data set itself.</p>
Input data for article "Large eddy simulation of the optimal street-tree layout for pedestrian-level aerosol particle concentrations"
<p>Input dataset used when performing LES simulations for journal article "Large eddy simulation of the optimal street-tree layout for pedestrian-level aerosol particle concentrations" (Karttunen et al., in preparation). The dataset was used with the PALM model system revision 3698 and most likely it won't work on older or newer versions.</p> <p>Instructions for use:<br> A precursor run must be run first. Output data (BINOUT) of it should be linked into a BININ directory of the actual scenario runs. You'll most likely have to tweak the CPU grid settings in ENVPAR and PARIN files in order to fit them to your computational resources. For more information on usage please refer to the PALM model documentation available online in <a href="https://palm.muk.uni-hannover.de/trac/wiki/doc">https://palm.muk.uni-hannover.de/trac/wiki/doc</a>.</p>
Online repository input data collection framework
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Necessary input data for AgriculturalData
<p>Necessary input data, that are needed to run the AgriculturalData, which computes the input time series for the agricultural trade models Agrimate, TWIST, and multiTWIST.</p> <p>Updated data will be renewed depending on the version.</p>
Input data and code related to "Utilizing curtailed wind and solar power to scale up electrolytic hydrogen production in Europe"
<p>Datasets and code for the submitted article: "Utilizing curtailed wind and solar power to scale up electrolytic hydrogen production in Europe" </p> <p>by Alissa Ganter<sup>1,2</sup>, Tyler H. Ruggles<sup>2</sup>, Paolo Gabrielli<sup>1</sup>, Giovanni Sansavini<sup>1,*</sup>, Ken Caldeira<sup>2</sup></p> <p><sup>1</sup> Institute of Energy and Process Engineering, ETH Zurich, 8092 Zurich, Switzerland</p> <p><sup>2</sup> Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA</p> <p><sup>*</sup> Corresponding author: email - sansavig@ethz.ch</p> <p>All rights lie with the authors. Refer to the README.docx for a description of the datasets and their usage in the article.</p>
Input data for the exposure assessment case study on air pollution and noise for the province of Utrecht, the Netherlands
<p>Input datasets for the case study described in the manuscript "A computational framework for agent-based assessment of multiple environmental exposures".<br>Use the free 7-Zip to uncompress. Uncompressed size ca 103 GiB.</p> <p>The datasets are licensed under a Creative Commons license (CC-BY 4.0). Contact: o.schmitz@uu.nl</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.