Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
38
datasets available to search
ShareScore release 0.9.0
Dataset results
38 results for “Model Repository”
Model data repository of "The role of sediment accretion and buoyancy on subduction dynamics and geometry"
<p>This dataset contains the code and data used in Brizzi et al. (2021): The role of sediment accretion and buoyancy on subduction dynamics and geometry</p>
A calibrated groundwater model (Modflow-NWT) data repository in the Koga Irrigation Project area, Ethiopia
<p>The repository includes the research data pertaining to the Modflow-NWT based groundwater model developed for the Koga irrigation project area, Ethiopia. The database constitutes three archived data folders namely, 1. MainData (mostly excel files which include model forcings, data used in model calibration, citizen science data, etc.), 2. GIS (mostly geospatial files to assist readers with the spatial locations of the irrigation project structures, as well as the important data and administrative locations), 3. ModelFiles (mostly text files which include model inputs and outputs).</p> <p>The data has been used in preparation of the manuscript titled, "A numerical framework to advance agricultural water management under hydrological stress conditions in a data scarce environment", published in the Agricultural Water Management journal (<a href="http://dx.doi.org/10.1016/j.agwat.2021.106947">10.1016/j.agwat.2021.106947</a>). Readers are requested to go through this article to find more details on the data. The model simulations ranged from 1st January 2008 to 15th August 2019.</p> <p> </p>
Data repository for Lin et al. (2022) "Thermospheric neutral density variation during the "SpaceX" storm: Implications from physics-based whole geospace modeling"
This dataset contains the necessary data and plotting tools supporting the paper titled "Thermospheric neutral density variation during the "SpaceX" storm: Implications from physics-based whole geospace modeling", by Lin et al., 2022. The data set contains thermospheric mass density simulated by MAGE, TIEGCM, DTM, and MSIS for the 1-6 February 2022 geomagnetic storm event.
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>
Extracting Enhanced Artifical Intelligence Model Metadata from Software Repositories
<p>Replication set for evaluations performed in EMSE submission "Extracting Enhanced Artifical Intelligence Model Metadata from Software Repositories" </p>
Automated Extraction of Artificial Intelligence Model Metadata from Repositories
<p>Replication datasets for MSR submission: "Automated Extraction of Artificial Intelligence Model Metadata from Repositories"</p> <p>This package contains the following:</p> <p>1. The model zoo dataset of 277 repository URLs.<br> 2. The arXiv dataset of 1,398 repository URLs extracted from arXiv papers.<br> 3. The annotated evaluation samples for both datasets with incorrect and missing properties marked per model.<br> </p>
Screencast of Automatic Building of a Repository for Component-based Synthesis of Warehouse Simulation Models
<p>Screencast of the migration of an existing simulation model into a software product line.</p>
Nordic44 - 2015 Powerflow Data: An Open Data Repository of an Equivalent Nordic Grid Model Matched to Historical Electricity Market Data for 2015
<p>This repository is used to provide documentation related to the model and data development process, provide source (raw) data for the model in different forms (i.e. Modelica, CIM 14, and PSS/E) for an equivalent Nordic grid model that has been matched to historical power flow data.</p> <p>The repository is documented in the paper below, see [Ref00].</p> <p><strong>Using this model, data or related software = cite our publications!</strong></p> <p>We are happy to contribute with this dataset, however, if you use any of the data or software provided, we will appreciate if you cite the following publications, as follows:</p> <p>A) Cite that "the raw and processed data files corresponding to the model are available as an open data set and documented in [Ref00]."</p> <p>B) Cite that the first appearance of the model, i.e. "the model is first presented in [Ref01]"</p> <p>[Ref00] L. Vanfretti, S.H. Olsen, V. S. Narasimham Arava, G. Laera, A. Bibadafar, T. Rabuzin, H. Jackobsen, J. Lavenius, and M. Baudette, "An Open Data Repository and a Data Processing Software Toolset of an Equivalent Nordic Grid Model Matched to Historical Electricity Market Data," submitted for publication, Data in Brief, 2016.</p> <p>[Ref01] L. Vanfretti, T. Rabuzin, M. Baudette, M. Murad, iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations, SoftwareX, Available online 18 May 2016, ISSN 2352-7110, http://dx.doi.org/10.1016/j.softx.2016.05.001.</p> <p><strong>Acknowledgment:</strong></p> <p>This model was originally developed in the context of the FP7 iTesla project, and further extended within the ITEA3 openCPSproject.</p> <p>Structure of the repository:</p> <p><strong>01_PSSE_Resources</strong>:</p> <ol> <li> <p><strong>Models</strong> :</p> <ul> <li> <p>A folder with PSS/E files of the base case</p> </li> <li> <p>A folder with a 7zip archive containing files of the original N44 system that has been modified to have the PSS/E base case</p> </li> </ul> </li> <li> <p><strong>Snapshots</strong> :</p> <ul> <li> <p><strong>N44_2015xxxx</strong> are folders named according to the day they refer to (for example <em>N44_20150401</em> refers to the 1st of April 2015). In each folder there are Excel files (<em>Consumption_xx.xlsx</em>, <em>Exchange_xx.xlsx</em>, <em>Production_xx.xlsx</em>) with data downloaded from Nord Pool website, an Excel file (<em>PSSE_in_out.xlsx</em>) summarizing the results from the Python script <em>Nordic44.py</em> in the folder <strong>04_Python_Resources</strong>, PSS/E snapshots for each hour before solving the power flow (<em>hx_before_PF.raw</em>) and after solving the power flow (<em>hx_after_PF.raw</em>)</p> </li> <li> <p><em>N44_BC.sav</em> is the PSS/E solved base case that Python script <em>Nordic44.py</em> (put the reference)</p> </li> </ul> </li> </ol> <p><strong>02_CIM14_Snapshots</strong>:</p> <ul> <li> <p><strong>N44_2015xxxx</strong> are folders named according to the day they refer to (e.g. <strong>N44_20150401</strong> refers to the 1st of April 2015). In each folder there are CIM files for each hour (<em>N44_hx_EQ.xml</em>, <em>N44_hx_SV.xml_, _N44_hx_TP.xml</em>)</p> </li> <li> <p><strong>N44_noOL_RDFIDMAP.xml</strong> is the file with IDs mapping of those cases (<em>N44_hx_noOL_EQ.xml</em>, <em>N44_hx_noOL_SV.xml</em>, <em>N44_hx_noOL_TP.xml</em>) with fixed overloading problems.</p> </li> <li> <p><strong>N44_RDFIDMAP_2015-1.xml</strong> and <strong>N44_RDFIDMAP_2015-2.xml</strong> are the files with IDs mapping of the remaining snapshots from 2015</p> </li> </ul> <p><strong>03_Modelica</strong>:</p> <ol> <li> <p><strong>iTesla_Platform</strong></p> <ul> <li> <p><strong>iPSL</strong> folder contains the version of the library which can be used to simulate snapshots generated from the iTesla Platform</p> </li> <li> <p><strong>Modelica_snapshots</strong> Modelica models generated from the snapshots by iTesla Platform</p> </li> </ul> </li> <li> <p><strong>SmarTSLab</strong></p> <ul> <li> <p><strong>OpenIPSL</strong> folder contains the version of the forked iPSL library which can be used to simulate the manually generated Modelica model of N44 with the record structures corresponding to the snapshots</p> </li> <li> <p><strong>Snapshots</strong> folder contains Modelica records automatically generated from the PSS/E records</p> </li> <li> <p><em>N44_Base_Case.mo</em> is the handmade N44 model with the loaded record of the power flow results from the PSS/E base case. It can be used to load other PF results from the folder <strong>03_Modelica/Snapshots</strong></p> </li> </ul> </li> </ol>
ShapeNet: An Information-Rich 3D Model Repository
Open the record for dataset details and reuse information.
EIAH data model: semantic interoperability between distributed digital repositories
<p>The authors described their information architecture project aimed at improving access to the Encyclopaedia of Iranian architectural history (EIAH) by signalling relationships between concepts and between concepts and documents. The outcome will be presented in a semantic portal or might be used for complex search queries by end users.</p>
Data repository in support of the article: Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemical transport model using Cloud-J v7.3e
<p>This dataset contains the measurement data, model outputs and Python (v3.10) scripts that are used to produce figures and tables in the paper: Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemical transport model using Cloud-J v7.3e.</p> <p>The newly created modules providing the interface with Cloud-J in the EMEP MSC-W and BoxChem models are called CloudJ_mod.f90.</p> <p>The measurement data and supporting MATLAB scripts used to create the ATom-1 data files read in by the Python scripts provided here, can be downloaded from https://doi.org/10.3334/ORNLDAAC/1651</p> <p> </p>
Data Repository for "Integrating Water Quality Data with a Bayesian Network Model to Improve Spatial and Temporal Phosphorus Attribution: Application to the Maumee River Basin"
<p>Data for "Integrating Water Quality Data with a Bayesian Network Model to Improve Spatial and Temporal Phosphorus Attribution: Application to the Maumee River Basin". This repository contains all the processed data used in the simulation (in "processed" folder), part of the raw data (in "raw" folder), and the SWAT simulation results (in "SWAT" folder). The code for processing the raw data, which are either provided here or publicly available online, is provided in the <a href="https://doi.org/10.5281/zenodo.8132662">code repository</a>. The links to the publicly available raw data are also provided in the code repository.</p>
Data repository of model outputs in Ferrier and Perron (2020), "The importance of hillslope scale in responses of chemical erosion rate to changes in tectonics and climate"
<p>This is a repository of model outputs in Ferrier and Perron (2020), "The importance of hillslope scale in responses of chemical erosion rate to changes in tectonics and climate" at the Journal of Geophysical Research - Earth Surface. See the readme file for descriptions of the data contained in each file.</p>
[DEPRECATED] Theislab sfaira Model Repository
<p>THIS WEIGHTS REPOSITORY IS NO LONGER COMPATIBLE WITH THE CURRENT VERSION OF SFAIRA. PLEASE FIND THE LATEST VERSION HERE: https://doi.org/10.5281/zenodo.4836516<br> <br> This is the official model weights repository provided with the <a href="https://github.com/theislab/sfaira">sfaira</a> python package. sfaira is a data and model zoo for single-cell RNA-seq data developed in the group of Prof. Fabian Theis at Helmholtz Munich. * = These authors contributed equally.</p>
Repository for: "Extreme statistic and extreme events in dynamical models of turbulence"
<div>This repository contains underlying data, post-processing scripts and figure scripts, corresponding to the article "Extreme statistic and extreme events in dynamical models of turbulence", X.M. de Wit, G. Ortali, A. Corbetta, A.A. Mailybaev, L. Biferale, F. Toschi, 2024, Phys. Rev. E 109 (5), 055106.</div> <div> </div> <div><strong>Data</strong></div> <div>Raw data of the obtained moments and histogram of the structure function are provided in 'PRODUCTION/STAT_RUNS/' and 'VALIDATION/STAT_RUNS/' respectively for the production runs and validation runs.</div> <div> </div> <div><strong>Post-processing</strong></div> <div>Various post-processing routines for e.g. the computation of the anomalous scaling exponents are provided in the Jupyter notebooks 'PROD_process.ipynb' and 'VALI_*_process.ipynb' respectively for the production runs and validation runs. The computation of the singularity spectrum is provided in 'PROD_singularity_spec.ipynb'.</div> <div> </div> <div><strong>Figures</strong></div> <div>Reproduction of the figures as appearing in the paper can be done using the corresponding Jupyter notebooks labeled as 'PAPER_*.ipynb'.</div>
Replication Package for 'Exploring the Carbon Footprint of Hugging Face's ML Models: A Repository Mining Study'
<p>Replication Package attached to the 'Exploring the Carbon Footprint of Hugging Face's ML Models: A Repository Mining Study' article. Within the README and accompanying scripts, you will find detailed instructions to guide you through the analysis conducted in the article.</p>
Pre-Clinical Models in Gynecological Tumors A Tissue Repository
ClinicalTrials.gov study NCT00250783. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Complementary Data and Model Repository for the Publication: "Comparison of methods to calculate groundwater recharge for karst aquifers under Mediterranean climate"
<p>This repository provides the resources related to the publication "Comparison of methods to calculate groundwater recharge for karst aquifers under Mediterranean climate." It includes the data sets used in the study, the SWAT model and python script for evaluation of the different methods compared in this study.</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.