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5,805 results for “Data model”
Simulation data from the three-dimensional multifluid MHD model of Najib et al. (2011)
<p>Simulation data from the three-dimensional multifluid MHD model of Najib et al. (2011).</p> <p>We use the data to study the ion escape at Mars.</p> <p> </p>
Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model - Data
<p>This repository contains the data and additional information for the paper 'Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model'. </p> <p>The following files are included:</p> <ul> <li>accuracy.zip: raw performance files for all models;</li> <li>plots.zip: additional plots;</li> <li>tuning.zip: tuning log files.</li> </ul>
Evaluating Text-to-Image Diffusion Models for Texturing Synthetic Data
<p>Data accompanying our paper on: <em>Evaluating Text-to-Image Diffusion Models for Texturing Synthetic Data</em></p> <p> </p> <p><a href="https://github.com/tlpss/diffusing-synthetic-data" target="_blank" rel="noopener">github repository</a></p> <p>meshes.zip contains the 3D meshes used to generate the synthetic data for all three object categories</p> <p>real-datasets.zip contains the real-world image datasets gathered to evaluate the synthetic data</p> <p> </p> <p> </p>
Meteorological data_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Meteorological data_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
Data for "FC2DES: Modeling 2D electronic spectroscopy for the Generalized Brownian Oscillator Molecular Hamiltonian"
<p>Within is the 2DES presented in the manuscript: "FC2DES: Modeling 2D electronic spectroscopy for the Generalized Brownian Oscillator Molecular Hamiltonian" as well as the parameter and input files used to create the spectra via the Python code package MolSpecPy.</p>
AIMD training data for H2 adsorption on MoxCy facets for machine learning model
<p>This data is used to train the MACE model for modeling hydrogen dissociation on molybdenum carbide surfaces.</p>
Multivariate Ordinary Least Squares (OLS) regression-based Seismic Hazard Model Data
<p>This dataset includes earthquake parameters, slab geometry, gravity anomalies, and fault proximities used for seismic hazard modeling in the Makran Subduction Zone (MSZ). Supplementary Table S1 contains earthquake data (location, depth, magnitude), slab properties (depth, dip, thickness, strike), and distances to key faults. Supplementary Table S2 provides intraslab seismicity, slab geometry, trench distances, and gravity data. The data are sourced from the USGS Earthquake Catalog, IRIS, Slab-2 model, GMRT, and other geophysical models.</p>
Data associated to the article "DFT-based Polarizable Ion Models for Molten Rare-earth Chlorides: from Lanthanum to Europium"
<p>Contains input file used to generate the results of the article:</p> <p>DFT-based Polarizable Ion Models for Molten Rare-earth Chlorides: from Lanthanum to Europium</p> <p>Kateryna Goloviznina, Maria-Chiara Notarangelo, Julien Tranchida, Emeric Bourasseau, Mathieu Salanne</p> <p>The files <em>data.inpt</em> and <em>runtime.inpt </em>are used to simulate the system using the software MetalWalls (available at https://gitlab.com/ampere2/metalwalls)</p>
Data for "Improved simulation of Madden–Julian Oscillation with the modified moist physical parameterizations for a global climate model"
<p>Model output data for the manuscript "Improved simulation of Madden–Julian Oscillation with the modified moist physical parameterizations for a global climate model", including convective precipitation (PRECC), large-scale precipitation (PRECL), mean SST and U850, <span>column-integrated MSE tendency anomalies, and boundary layer moisture convergence. </span></p>
Data for Influence of Coverage Dependence on the Thermophysical Properties of Adsorbates and its Impact on Microkinetic Models
<p>Data and scripts for the preprint "Influence of Coverage Dependence on the Thermophysical Properties of Adsorbates and its Impact on Microkinetic Models".</p>
FESOM-REcoM model data: Predicting future distribution of Antarctic toothfish (Dissostichus mawsoni), with implications for Marine Protected Areas in the Southern Ocean
<p>This data set belongs to <strong>"Predicting future distribution of Antarctic toothfish (<em>Dissostichus mawsoni</em>), with implications for Marine Protected Areas in the Southern Ocean"</strong> by <a>Rebecca Konijnenberg, Cara Nissen, Casper Kraan, Jilda Cavacco, Peter Yates, Philippe Ziegler, and Katharina Teschke (in preparation). </a></p> <p>Contact for data set: cara.nissen@colorado.edu</p> <p>The data provided here are post-processed from the raw FESOM1.4-REcoM2 model output which can be obtained <br>at the World Data Center for Climate (WDCC): <a href="https://www.wdc-climate.de/ui/project?acronym=HighRes_highLat_SO">https://www.wdc-climate.de/ui/project?acronym=HighRes_highLat_SO</a></p> <p>simA (historical simulation): <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_hist_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_hist_vA_vC</a><br>simA-ssp126: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s126_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s126_vA_vC</a><br>simA-ssp245: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s245_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s245_vA_vC</a><br>simA-ssp370: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s370_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s370_vA_vC</a><br>simA-ssp585: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s585_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s585_vA_vC</a><br>simB (control simulation): <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_B_1921_cA_cC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_B_1921_cA_cC</a></p> <p>Here, we provide decadal monthly climatologies of the following variables: sea-ice fraction, surface small-phytoplankton chlorophyll, surface diatom chlorophyll, as well as potential temperature, practical salinity and oxygen concentrations (all at the surface, at the bottom, at 100m, at 250m, at 500m, at 1000m, and at 1500m). For example, "tos" is temperature in ocean at surface", while "tob" is "temperature in ocean at bottom" (with <em>bottom</em> here being the deepest available model grid cell at each location).</p> <p>We also provide the script used to re-grid the original model output to the regular 0.25° x 0.0625° mesh used in this study. </p>
Supplementary data: Optimising centralisation and decentralisation in distribution networks for perishable products through mathematical modelling, parametric analysis, and machine learning
<p><span>The success of distribution companies for perishable products is enabled by optimally configuring distribution networks, which allows for reducing total logistic costs while ensuring reduced product spoilage and high service levels. Since customer demand for perishable products varies over time, the network configuration should not be optimised once, but periodically reviewed. Among the decisions to be reviewed, determining whether to centralise or decentralise inventory (i.e., stock allocation in distribution centres) is crucial. However, the literature overlooks stock allocation decisions, and existing methodologies to compare the economic performance of centralised, decentralised, and hybrid policies neglect important cost items, also requiring advanced computational technologies and skills to be applied. This paper addresses these gaps by providing two contributions. In this dataset, a comparison has been made between the cost performance of centralized, decentralized, and hybrid stock allocation policies in distribution networks for perishable products. The dataset comprises 100,000 realistic case studies generated through a Sobol quasi-random low discrepancy series.</span></p>
Raw IMC files for Spatial subsetting enables integrative modeling of oral squamous cell carcinoma multiplex imaging data.
<p>Raw MCD files for the Stanford cohort of oral squamous cell carcinoma patients in this publication:</p> <p>Spatial subsetting enables integrative modeling of oral squamous cell carcinoma multiplex imaging data (DOI:<span> <a href="https://doi.org/10.1016/j.isci.2023.108486" target="_blank" rel="noopener">10.1016/j.isci.2023.108486</a>).</span></p>
AN EXTENSION OF N-MIXTURE OCCUPANCY MODELS FOR COUNT DATA
Open the record for dataset details and reuse information.
Netzero2040: Reaching climate neutrality in Austria by 2040: engaging stakeholders for model-supported scenario development. Data repository
<p><span>This repository contains scenario results in pyam format, qualitative scenario narratives and drivers identified by stakeholders for the NetZero2040 project.</span></p> <p><span>NetZero2040 developed the first independent scenarios achieving climate-neutrality in Austria by 2040. We improve on previous analyses by employing a structured co-creation process involving stakeholders and modellers, simultaneously modelling the whole energy system and the electricity system in great detail, creating shared visions of a climate-neutral future. Results are openly available and have been broadly disseminated in the scientific community and to the public. Our scenarios are differentiated by assumptions on energy demand and imports of energy carriers. They show that a rapid electrification of transport and heating, in combination with a build out rate of renewable energies which is well above historical maxima in the Austrian power system, allow significant emission reductions until 2030, and that these measures are consistently required in all scenarios. However, after 2030 scenarios diverge and uncertainty about the most cost-efficient transformation measures prevail. </span></p>
Codes and data for ARA model
<h5>Codes and data for the Adhesion-Repulsion-Attraction model</h5> <div>by Hideki Murakawa, Jose A. Carrillo, Makoto Sato, Miaoxing Wang</div>
Including population and environmental dynamic heterogeneities in continuum models of collective behaviour with applications to locust foraging and group structure Data and Code
<p>This dataset includes all data used for the creation of "Including dynamic population and environmental heterogeneity in continuum models of collective behaviour with applications to locust foraging and group structure" as well as a snapshot of the code used.<br><br>Each zip should be unzippable and the code should operate with only the contents of the zip file.</p>
Stable Machine-Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection-Permitting Simulations: Data and Visualization Notebooks
<p>The data, jupyter notebooks, and saved model weights for the "Stable Machine-Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection-Permitting Simulations" Hu et al. (2025) arxiv preprint: <a href="https://arxiv.org/abs/2407.00124">arXiv:2407.00124</a>. This updated version contains more analysis notebooks together with related data/model.</p>
Compendium of R code and data for Mycenaean roads in the Peloponnese, Greece: least-cost path modelling using R and Movecost
<p><strong>Abstract</strong></p> <p><em>This study evaluates multiple methodologies and their variants for Least Cost Path (LCP) modelling, applied in combination with different Digital Elevation Models (DEMs), to explore the broader applicability of the Movecost package, using the Mycenaean road networks of the Peloponnese (Greece) as case studies. Using a geographic information system (GIS) and the R programming environment, this paper employs the Movecost package for the R statistical package to simulate ancient routes based on existing road segments. By integrating a variety of functions and parameters, this study evaluates their effectiveness across different DEMs, including both Shuttle Radar Topography Mission DEM (SRTM-DEM) and Copernicus DEM (COP-DEM) at 30 m spatial resolution. The study also examines how varying these parameters can lead to different modelling outcomes, underscoring the necessity of calibrating least-cost analysis to specific regional contexts. The road segments around Nichoria (Messenia), Ayios Ioannis Kazarma (Argolis), and in the Berbati Valley (Argolis), provide a historical canvas against which these methodological innovations are tested with the ultimate aim of exploring the capabilities of the Movecost package and how different combinations of DEM, function, parameter, and path points can effectively model the route through the existing road remains, highlighting the variability and context-specific nature of LCP modelling. The results suggest that the 'Wheeled-vehicle critical cost function' (WCS) was effective in modelling the roads through the extant remains based on start and endpoints suggested by previous research and posited by this paper. These results further suggest that Mycenaean roads likely served as key infrastructure links between major centres and ports or harbours, underscoring their role in facilitating regional trade and communication. However, this outcome represents one of several possible results, as the appropriateness of functions and the parameters tested depend on the specific landscape and archaeological context. This underscores the importance of careful parameter selection, providing insights into the economic and social landscapes of Mycenaean Greece, while also highlighting the potential of integrating spatial data with robust computational tools to enhance our understanding of ancient infrastructure.</em></p>
Data underlying research paper "Developing an open data intermediation business model: insights from the case of Esri"
<p><strong>Data underlying research paper “Developing an open data intermediation business model: insights from the case of Esri” </strong></p> <p>by Ashraf Shaharudin, Bastiaan van Loenen, and Marijn Janssen from Delft University of Technology (TU Delft), the Netherlands.</p> <p>This folder contains data underlying the research paper “Developing an open data intermediation business model: insights from the case of Esri”. It consists of:</p> <p>1. De-identified interview transcripts</p> <p>2. Informed consent form template</p> <p><strong>Note about the de-identified interview transcripts:</strong></p> <p>The de-identified interview transcripts should be read in the context of the research on open data ecosystem and the role of Esri as open data intermediaries.</p> <p>The 27 interviews, involving 29 interviewees, were conducted between April 2023 and April 2024 based on the semi-structured approach. We shared the tentative interview questions with the interviewees in advance (for the majority, at least three working days prior). Since they are semi-structured interviews, the ultimate interview questions may differ from the tentative questions.</p> <p>We removed personally identifiable information from the transcripts. Some interviewees may risk being identifiable if their organization is known. Hence, we removed the organization and country information from all transcripts. </p> <p>With verbal communication, some sentences may be less incomprehensible in writing. Thus, we did minimal edits when transcribing to improve the comprehensibility where necessary, but the main objective was to keep the transcripts as close to verbatim as possible. </p> <p><strong>Note about the informed consent form template:</strong></p> <p>We sent the informed consent form to every interviewee in advance and requested that they return it to us before or during the interview. </p> <p>All interviewees whose interview transcripts are recorded in this document give permission for the anonymized transcript of their interview, with personally identifiable information redacted, to be shared in 4TU.ResearchData repository so it can be used for future research and learning.</p> <p><strong>Acknowledgement:</strong></p> <p>This research is part of the 'Towards a Sustainable Open Data ECOsystem' (ODECO) project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 955569. The opinions expressed in this document reflect only the author’s view and in no way reflect the European Commission’s opinions. The European Commission is not responsible for any use that may be made of the information it contains.</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.