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.
867
datasets available to search
ShareScore release 0.9.0
Dataset results
867 results for “repositories”
Repository: Rayleigh-wave attenuation and phase velocity maps of the greater Alpine region from ambient noise
<p><br>Repository organized by Henrique Berger Roisenberg for the paper Roisenberg et al. (2024). The files are organized as follows:</p> <p><strong>Folders:</strong></p> <p><strong>-dispersion_curves:</strong><br>inside this folder there is a .zip file that contains all the dispersion curves calculated;</p> <p><strong>-attenuation:</strong><br>comprising three files with the results of attenuation calculations, i.e., the attenuation values, the grid, and the periods;</p> <p><strong>-c:</strong><br>comprising three files with the results of phase velocity calculations, i.e., the phase velocity values, the grid, and the periods;</p> <p><strong>-scripts: </strong><br>contains two python scripts, one called 'figures' to plot the figure 1, 4, and 6 of the paper, and another called 'alparray_computations' to perform the computations with the original alparray data, using seislib, resulting on the figures 2, 3, and 5 of the paper.</p> <p>Inside the folder '<strong>inputs</strong>' there are three folders that serve as input for the figures of the paper, to be used in the scripts. These are:</p> <p><strong>-raster: </strong><br>contains the topography raster used to plot the map of the study area;</p> <p><strong>-shapefiles:</strong><br>contains the shapefiles used in the regionalization analysis;</p> <p><strong>-station locations: </strong><br>contains the latitudes and longitudes of the stations used in this study.</p> <p> </p>
Image repository for "Towards advancing Translators' Guidance for Organisations Tackling Innovation Challenges in Manufacturing within an Industry 5.0 context"
<p>The files on this trusted repository are provided by the authors of the manuscript with the title “Towards advancing Translators’ Guidance for Organisations Tackling Innovation Challenges in Manufacturing within an Industry 5.0 context” that was received by the MDPI journal Sustainability (ISSN 2071-1050) on 29 January 2024, got the manuscript ID sustainability-2872279, and is intended to become part of the special issue “Sustainable Materials, Manufacturing and Design” accessible under the link <a href="https://www.mdpi.com/journal/sustainability/special_issues/Sus_materials_manufacturing_design">https://www.mdpi.com/journal/sustainability/special_issues/Sus_materials_manufacturing_design</a>.</p> <p>The authors Paul-Ludwig Michael Noeske, Alexandra Simperler, Welchy Leite Cavalcanti, Vinicius Carrillo Beber, Brendon Weager, Tasmin Alliott, Peter Schiffels, and Gerhard Goldbeck aim at facilitating common access to the files representing high-resolution microscopy images (corresponding to the light microscopy (LM) and scanning electron microscopy (SEM) images shown in Figure 9 and Figure 12 in the manuscript or complementing them) given in .jpg and .tif format, respectively. Moreover, this repository comprises a .csv file containing the data points underlying the values presented in Table A1 of this manuscript and their description. The authors indicate here that following the sixth step of the translation process in materials modelling the translator may provide these data in this presentation that is adapted to the process-centric perspective required by representatives of an enterprise manufacturing prepregs and to their background knowledge disclosed to the translator beforehand.“</p>
ODLEP Knowledge Repository
<p>The database contains three files:</p> <p>1) ALL_INSTRUCTORS_PF_FINAL.csv: it is a file with 275 answers to a survey that was developed in the context of the ODLEP project (<strong>Project reference No: 2022-1-EL01-KA220-HED-000089152</strong>) and </p> <p>The questionnaire includes one hundred questions, as mentioned earlier and it is divided into four discrete parts:</p> <ul> <li> <p>Participants’ Profile</p> </li> <li> <p>Distance Education Experience</p> </li> <li> <p>Learning and Teaching Styles</p> </li> <li> <p>Personality Characteristics</p> </li> </ul> <p>2) ALL_STUDENTS_FINAL_PF_FINAL.csv: <strong> Students from six universities participated in the research and 646 responses were collected. </strong></p> <p>The survey that the students answered consists of the following discrete parts:</p> <ul> <li> <p>Introductory note on the Specific Research Survey</p> </li> <li> <p>Students’ Attributes</p> </li> <li> <p>Students’ Distance Education Experience</p> </li> <li> <p>Students’ Preferred Learning Styles</p> </li> <li> <p>Fellow Students’ Preferred Learning Styles</p> </li> <li> <p>Preferred teaching style of Instructors as considered by students</p> </li> <li> <p>Students’ Personality (big five personality traits and facets)</p> </li> </ul> <p> </p> <p>3)ODLEP_Knowledge_repository_v2.xlsx: An excel file with two tabs. In the first tab 42 distance HE programs are summarized. The tab contains text that answers the following elements: Country, Program Name, Period that it was active, Characteristics that made it successful, Limiting Factors, Additional Information.</p> <p>In addition, the second tab contains information on 97 scientific papers on the issue of Distance/online education and the parameters that made it successful. The column names are: Title, Authors, Year of Publication, Journal Name, Objective of the paper, Most important Conclusions</p> <p> </p>
Github Repository for: European green crab predation in a Washington State estuary revealed with DNA metabarcoding
<p><strong>Fisher, MC, Grason, EW, Stote, A, Kelly, RP, Litle, K, & PS McDonald. (2024).<em> </em>Invasive European green crab (<em>Carcinus maenas</em>) predation in a Washington State estuary revealed with DNA metabarcoding. DOI:10.1371/journal.pone.0302518<em><br></em></strong></p> <p>Github release v1.1 of the repository for Fisher et al. 2024, "European green crab predation in a Washington State estuary revealed with DNA metabarcoding." For the most updated repository, see: <a href="https://github.com/mfisher5/Green-crab-dDNA/tree/main/doc">github.com/mfisher5/Green-crab-dDNA</a></p> <p>Contains the code and minimum dataset necessary to replicate study findings.</p> <p> </p> <p>---</p> <p>Abstract: Predation by invasive species can threaten local ecosystems and economies. The European green crab (<em>Carcinus maenas</em>), one of the most widespread marine invasive species, is an effective predator associated with clam and crab population declines outside of its native range. In the U.S. Pacific Northwest, green crab has recently increased in abundance and expanded its distribution, generating concern for estuarine ecosystems and associated aquaculture production. However, regionally-specific information on the trophic impacts of invasive green crab is very limited. We compared the stomach contents of green crabs collected on shellfish aquaculture beds versus natural intertidal sloughs in Willapa Bay, Washington, to provide the first in-depth description of European green crab diet at a particularly crucial time for regional management. We first identified putative prey items using DNA metabarcoding of stomach content samples. We compared diet composition across sites using prey presence/absence and an index of species-specific relative abundance. For eight prey species, we also calibrated metabarcoding data to quantitatively compare DNA abundance between prey items, and to describe an ‘average’ green crab diet at an intertidal slough and an actively cultivated Manila clam bed. From the stomach contents of 61 green crabs, we identified 54 unique taxa belonging to nine phyla. The stomach contents of crabs collected from cultivated Manila clam beds were significantly different from the stomach contents of crabs collected at natural intertidal sloughs. Across all sites, arthropods were the most frequently detected prey, with the native hairy shore crab (<em>Hemigrapsus oregonensis</em>) the single most common prey item. Of the eight species included in the quantitative model, two ecologically-important native species – the sand shrimp (<em>Crangon franciscorum</em>) and the Pacific staghorn sculpin (<em>Leptocottus armatus</em>) – were the most abundant in crab stomach contents, when present. In addition to providing timely information on green crab diet, our research demonstrates the novel application of a recently developed model for more quantitative DNA metabarcoding. This represents another step in the ongoing evolution of DNA-based diet analysis towards producing the quantitative data necessary for modeling invasive species impacts.</p>
Data and code repository for «Magnetic Order in Nanoscale Gyroid Netwoks»
<p>Data and Code repository for </p> <p>«Magnetic Order in Nanoscale Gyroid Netwoks»</p> <p>Ami S. Koshikawa, Justin Llandro, Masayuki Ohzeki, Shunsuke Fukami, Hideo Ohno, and Naëmi Leo</p> <p>Physical Review B 108, 024414 (2023)</p> <p>https://doi.org/10.1103/PhysRevB.108.024414</p>
Data and literature repository for "Climate Futures are Political Futures: Integrating Political Development Into the Shared Socioeconomic Pathways (SSPs)"
<p>The datasets provided in the repository (listed in Table 1 of the manuscript):</p> <ul> <li>Governance (Andrijevic et al., 2020)*</li> <li>Government effectiveness (Andrijevic et al., 2020)*</li> <li>Violent conflict (Hegre et al., 2016)</li> <li>Rule of law (update to the Soergel et al., 2021)</li> </ul> <p>*Please note that these two variables can be found in the same data file.<br><br></p> <p>The indicators can also be retrieved through the <a href="https://ssp-extensions.apps.ece.iiasa.ac.at/">SSP Extensions Explorer.</a> <br><br><strong><br>For applications of the projections of political indicators in further analyses, please consult the following references: </strong> </p> <p>Brutschin, E., Pianta, S., Tavoni, M., Riahi, K., Bosetti, V., Marangoni, G., & Van Ruijven, B. J. <a href="https://iopscience.iop.org/article/10.1088/1748-9326/abf0ce/meta">A multidimensional feasibility evaluation of low-carbon scenarios.</a> <em>Environmental Research Letters </em>2021, <em>16</em>(6), 064069.</p> <p>Gidden MJ, Brutschin E, Ganti G, Unlu G, Zakeri B, Fricko O<em>, et al. </em><a title="https://iopscience.iop.org/article/10.1088/1748-9326/acd8d5" href="https://iopscience.iop.org/article/10.1088/1748-9326/acd8d5">Fairness and feasibility in deep mitigation pathways with novel carbon dioxide removal considering institutional capacity to mitigate</a>. <em>Environmental Research Letters </em>2023, <strong>18</strong>(7)<strong>: </strong>074006. </p> <p>Hoch JM, de Bruin SP, Buhaug H, Von Uexkull N, van Beek R, Wanders N. <a title="https://iopscience.iop.org/article/10.1088/1748-9326/ac3db2" href="https://iopscience.iop.org/article/10.1088/1748-9326/ac3db2">Projecting armed conflict risk in Africa towards 2050 along the SSP-RCP scenarios: a machine learning approach</a>. <em>Environmental Research Letters </em>2021, <strong>16</strong>(12)<strong>: </strong>124068. </p> <p>Joshi DK, Hughes BB, Sisk TD. <a title="https://www.sciencedirect.com/science/article/abs/pii/S0305750X15000145" href="https://www.sciencedirect.com/science/article/abs/pii/S0305750X15000145">Improving governance for the Post-2015 Sustainable Development Goals: Scenario forecasting the next 50 years</a>. <em>World Development </em>2015, <strong>70: </strong>286-302. </p> <p>Moyer JD. <a title="https://www.sciencedirect.com/science/article/pii/S0305750X23000062" href="https://www.sciencedirect.com/science/article/pii/S0305750X23000062">Blessed are the peacemakers: The future burden of intrastate conflict on poverty</a>. <em>World Development </em>2023, <strong>165: </strong>106188. </p> <p>Moyer JD, Turner SD, Meisel CJ. <a title="https://journals.sagepub.com/doi/abs/10.1177/0022343320929740" href="https://journals.sagepub.com/doi/abs/10.1177/0022343320929740">What are the drivers of diplomacy? Introducing and testing new annual dyadic data measuring diplomatic exchange</a>. <em>Journal of Peace Research </em>2021, <strong>58</strong>(6)<strong>: </strong>1300-1310. </p> <p>Petrova, K, Olafsdottir, G, Hegre, H, Gilmore, EA (2023). <a title="https://iopscience.iop.org/article/10.1088/1748-9326/acb163" href="https://iopscience.iop.org/article/10.1088/1748-9326/acb163">The ‘conflict trap’ reduces economic growth in the shared socioeconomic pathways</a>. <em>Environmental Research Letters</em>, 2023, <strong>18</strong>(2), 024028. </p>
Data Repository submission for "The influence of density driven mixing mechanisms on ureolysis induced carbonate precipitation"
<p>This folder includes the data and files that support the manuscript titled "The Influence of Density-Driven Mixing Mechanisms on Ureolysis-Induced Carbonate Precipitation". Please see included Readme for more information.</p>
Digital repository for: Large-scale forest disturbance and associated management shape bird communities in Central European spruce forests
<p>Repository containing R-script and data to reproduce analysis and main figures on the effect of large-scale forest disturbance and associated pre- and post-disturbance management on bird communities in the Harz Mountains, Germany.</p> <p>R-script includes:</p> <ul> <li>indicator species analysis (R package indicspecies; Cáceres & Legendre, 2009)</li> <li>non-metric multidimensional scaling (R package vegan; Oksanen et al., 2016)</li> <li>rarefaction- and extrapolation of Hill numbers (R package iNEXT; Hsieh et al., 2019)</li> <li>multi-species community distance sampling (R package sp Abundance; Doser et al., 2023)</li> </ul> <p>Attached files:</p> <ul> <li><strong>bird_data_Graser_et_al.csv </strong>(row data of bird species point counts per distance category)</li> <li><strong>bird_data_abundance_100_Graser_et_al.csv </strong>(abundance of species per sampling site, summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>siteCovs_Graser_et_al.csv</strong> (environmental variables for each sampling point)</li> <li><strong>A_species_matrix_100_new_Graser_et_al.csv</strong> (species-site matrix of <strong>bark-beetle disturbance, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>B_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>windthrow disturbance, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>C_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle/windthrow disturbance, underplanted, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>D_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle /windthrow disturbance, salvage-unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>E_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle /windthrow disturbance, underplanted, salvage-unlogged </strong>sites for rarefaction and extrapolation, summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong> F_species_matrix_100_new_Graser_et_al.cs</strong>v (species-site matrix of <strong>mature spruce plantation </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>msHDS_bird_data_management_model_Graser_et_al.rds</strong> (R-data set for multi-species community distance sampling of the effect of different pre- and post-disturbance management groups)</li> <li><strong>msHDS_bird_data_stand_age_model_Graser_et_al.rds </strong>(R-data set for multi-species community distance sampling of the effect of post-disturbance forest succession)</li> </ul> <p>A more detailed description of the data can be found in the README.txt document.</p> <p><span>References:</span></p> <p><span>Cáceres, M. D., & Legendre, P. (2009). </span><span>Associations between species and groups of sites: Indices and statistical inference. <em>Ecology</em>, <em>90</em>(12), 3566–3574. https://doi.org/10.1890/08-1823.1</span></p> <p><span>Doser, J. W., Finley, A. O., Kéry, M., & Zipkin, E. F. (2023). spAbundance: An R package for single‐species and multi‐species spatially explicit abundance models. <em>Methods in Ecology and Evolution</em>, <em>15</em>(6), 1024–1033. https://doi.org/10.1111/2041-210X.14332</span></p> <p><span>Hsieh, T. C., Ma, K. H., & Chao, A. (2019). <em>iNEXT-package: Interpolation and extrapolation for species diversity</em>. https://cran.r-project.org/web/packages/iNEXT/vignettes/Introduction.html</span></p> <p><span>Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P., O’hara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H., Wagner, H., Minchin, P. R., Gavin, L., & Henry, H. (2016). Vegan: Community ecology package. R package version 1.17-4. <em>Http://CRAN. R-Project. </em></span><em><span>Org/Package=vegan</span></em><span>.</span></p> <p></p> <p></p>
Data repository for "Genesis and timing of KREEP-free lunar Mg-suite magmatism indicated by the first norite meteorite Arguin 002"
<p>This is the data repository for paper entitled "Genesis and timing of KREEP-free lunar Mg-suite magmatism indicated by the first norite meteorite Arguin 002". This data repository includes two EXCEL (.xlsx) files representing the dataset necessary to interpret, replicate and build upon the methods or findings reported in the article.</p> <p>Regarding the EXCEL file named "Supplementary Data 1", it incorporates the mineral EPMA compositions (Table S1), mineral trace-element compositions (Table S2), bulk chemistry (Table S3), SIMS U-Pb results (Table S4), and mineral modal abundances and the launch-region identification results (Table S5) in the comprehensive study of the lunar norite meteorite, Arguin 002.</p> <p>Regarding the EXCEL file named "Supplementary Data 2", it incorporates analyses of reference materials in EPMA (Table S1), LA-ICP-MS (Table S2), ICP-MS (Table S3), and SIMS (Table S4).</p>
NAPRORE-CR (NAtural PROducts REpository - Costa Rica)
<p><strong>Costa Rica</strong> is one of the countries with the greatest biodiversity in the world, thus <strong>NAPRORE-CR</strong> was born as a need to make an inventory of the wealth of isolated and identified natural products in Costa Rica.</p> <p>Within the aims of this repository:</p> <ol> <li> <p>Create an open access repository where natural products isolated and identified in Costa Rica can be found.</p> </li> <li> <p>Characterize the chemical diversity of the compounds in the database using chemoinformatic tools and thus be able to serve as a reference source for the design of new drugs and biomaterials.</p> </li> <li> <p>Be part of and contribute to the <strong>Latin American Natural Product Database (LANaPD)</strong></p> </li> </ol> <p><strong>NAPRORE-CR</strong> was designed and developed in collaboration with the research group of Dr. Jose Medina-Franco from the UNAM. We will shortly release more details about the database in a publication.</p>
Data & code repository for "A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation"
<p>This repository includes the data and code that can be used to reproduce the figures for the paper entitled <em>A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation</em>.</p>
Open-Source Terraform Repositories - SAST (tfsec, terrascan, checkov) vulnerability snapshot
<p>Vulnerability findings of open-source Terraform repositories in GitHub, collected with 3 static-code analysis tools (tfsec, terrascan, checkov).</p>
Data Repository for "Single-particle characterization of polycyclic aromatic hydrocarbons in background air in Northern Europe", Atmos. Chem. Phys.
<p>Data Repository for <br> Passig et al., "Single-particle characterization of polycyclic aromatic hydrocarbons<br> in background air in Northern Europe", Atmospheric Chemistry and Physics, 2021/22</p> <p>Details in Readme.txt</p> <p> </p>
Supplementary Repository S3
<p>SQL queries and query results that were used to estimate the precision of MAIA jobs with UnKnoT on <a href="https://biigle.de">biigle.de</a>.</p>
Supplementary Repository S2
<p>SQL queries, query results and Python code that were used to estimate the average "real world" annotation time on <a href="https://biigle.de">biigle.de</a>. User IDs were anonymized with consistend randomized IDs (using <code>anonymize-ids.py</code>).</p> <p>Example usage to reproduce the results:</p> <pre>python annotation-time.py annotation-time-anonymized.csv</pre>
Supplementary Repository S6
<p><a href="https://github.com/open-mmlab/mmdetection">MMDetection</a> configs and inference results of four object detection methods for comparison with <a href="https://doi.org/10.1371/journal.pone.0207498">MAIA</a> and <a href="https://doi.org/10.1109/ACCESS.2020.3014441">UnKnoT</a>.</p> <p>The <code>inference.py</code> script was used to perform the object detection with the trained models. The script requires MMDetection.</p>
Supplementary Repository S4
<p>Evaluation of <a href="https://doi.org/10.1371/journal.pone.0207498">MAIA</a> and <a href="https://doi.org/10.1109/ACCESS.2020.3014441">UnKnoT</a> object detection with different adjustments to the training procedure based on <a href="https://doi.org/10.3389/frai.2020.00049">IFeaLiD</a> visualizations.</p>
Model data repository of "Styles of Trench-parallel Mid-ocean Ridge Subduction Affect Cenozoic Geological Evolution in circum-Pacific Continental Margins"
<p>This dataset contains the data used in Wu et al. (2022): "Styles of Trench-parallel Mid-ocean Ridge Subduction Affect Cenozoic Geological Evolution in circum-Pacific Continental Margins".</p>
Cyclic unrest in a geothermal field as a harbinger of the Fagradalsfjall eruption, Iceland - INSAR data repository
<p>This repository is providing the InSAR data generated from the Copernicus Sentinel-1A and 1B satellites and as published in the paper</p> <p>Flóvenz et al. (2022) Cyclic unrest in a geothermal field as a harbinger of the Fagradalsfjall eruption, Iceland. Nature Geosciences, NGS-2021-06-01178</p> <p>We analyse deformation and seismicity for one year prior to the March 2021 Fagradalsfjall eruption in Iceland. We generate a high-resolution catalogue of 39,500 earthquakes using optical cable recordings and develop a poroelastic model to describe three pre-eruptional uplift and subsidence cycles at the Svartsengi geothermal field, 8 km west of the eruption site. We find the observed deformation is best explained by cyclic intrusions into a permeable aquifer by a fluid injected at 4 km depth below the geothermal field, with a total volume of 0.11±0.05 km3 and a density of 850±350 kg/m3.</p> <p>The geodetic data relevant for the publication and provided here include:</p> <p>1. Displacement from ascending geometry</p> <p>2. Displacement from descending geometry</p> <p>3. Vertical displacement component</p> <p>4. Horizontal displacement component</p> <p>These data are available for the following bands and dates:</p> <p>band date<br> 58 07-01-2020<br> 57 13-01-2020<br> 56 19-01-2020<br> 55 25-01-2020<br> 54 31-01-2020<br> 53 06-02-2020<br> 52 12-02-2020<br> 51 18-02-2020<br> 50 24-02-2020<br> 49 01-03-2020<br> 48 07-03-2020<br> 47 13-03-2020<br> 46 19-03-2020<br> 45 25-03-2020<br> 44 31-03-2020<br> 43 06-04-2020<br> 42 12-04-2020<br> 41 18-04-2020<br> 40 24-04-2020<br> 39 30-04-2020<br> 38 06-05-2020<br> 37 12-05-2020<br> 36 18-05-2020<br> 35 24-05-2020<br> 34 30-05-2020<br> 33 05-06-2020<br> 32 11-06-2020<br> 31 17-06-2020<br> 30 23-06-2020<br> 29 29-06-2020<br> 28 05-07-2020<br> 27 11-07-2020<br> 26 17-07-2020<br> 25 23-07-2020<br> 24 29-07-2020<br> 23 04-08-2020<br> 22 10-08-2020<br> 21 16-08-2020<br> 20 22-08-2020<br> 19 28-08-2020<br> 18 03-09-2020<br> 17 09-09-2020<br> 16 15-09-2020<br> 15 21-09-2020<br> 14 27-09-2020<br> 13 03-10-2020<br> 12 09-10-2020<br> 11 15-10-2020<br> 10 21-10-2020<br> 9 27-10-2020<br> 8 02-11-2020<br> 7 08-11-2020<br> 6 14-11-2020<br> 5 20-11-2020<br> 4 26-11-2020<br> 3 02-12-2020<br> 2 08-12-2020<br> 1 14-12-2020</p> <p> </p>
SILICOFCM_Virtual patients repository_clinical features
<p>Generation of a virtual dataset based on one of the integrated virtual generators into the SILICOFCM platform. The dataset contains 1000 virtually generated patients with 20 virtually generated clinical features by the real dataset of SILICOFCM: age, sex, NYHA class, systolic pressure, diastolic pressure, syncope, heart murmurs, left ventricular ejection fraction (LVEF or EFLV), left ventricular internal dimension at end-diastole (LVIDd), left ventricular internal dimension at end systole (LVIDs), intraventricular septal thickness at end-diastole (IVSd), posterior wall thickness at end-diastole (PLWd), endsystolic volume of left ventricle (SVLV), left ventricular outflow tract maximum pressure gradient (maxLVOTPG), Doppler E/E’ ratio (EE), body to mass index (BMI), left atrium size (LA), Alanine aminotransferase (ALT), aorta size (AO), and aortic valve (AV). The dataset can be utilized for Machine Learning modeling.</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.