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3,481 results for “data set”
Hintereisferner energy balance data set
<p>This resource provides meteorological and glaciological data from two automatic weather stations operated at Hintereisferner glacier (Austria). The data cover a full annual glaciological cycle (Oct. 2003- Nov. 2004) and allow for investigation of the year-round local meteorological conditions and surface exchange processes in the ablation and accumulation area of the glacier. The data may also be used to drive and validate respective numerical models.</p>
Interpreting accuracy revisted: A refined approach to interpreting performance analysis. Data set
<p>This data set contains data on interpreting accuracy of ten professional and ten student interpreters. Information on the level of expertise is contained in the filename: "student" refers to a student's rendition, "professional" to a rendition by a professional interpreting. The data set further includes information on:</p> <ul> <li>unit: The meaning unit in the source text (anonymized for rata protection resons)</li> <li>identfier: a number from 1 to 488 to identify each unit</li> <li>sentence: The full sentence taht contains the unit (anynomized for data protection reasons)</li> <li>rating: whether the unit was correctly (1) rendered, or incorrectly/missing (0),</li> <li>category: information about the category of the unit</li> <li>weighing: weighing assigned to each category</li> <li>score: score obtained for the unit</li> </ul> <p>For data protection reasons and in compliance with the declaration of Helsinki, the data set does not contain information about the source text or the rendition as a transcript.</p> <p>The data set is primarily used as an example data set to assess interpreting accuracy. Please also refer to the following publication:</p> <p></p> <div> <div>Gieshoff, A. C., & Albl-Mikasa, M. (2022). Interpreting accuracy revisited: a refined approach to interpreting performance analysis. <em>Perspectives</em>, <em>32</em>(2), 210–228. https://doi.org/10.1080/0907676X.2022.2088296</div> <div> </div> <div>The data set can be re-analysed using the following R-script: https://github.com/ac-gieshoff/interpreting-accuracy</div> </div> <p> </p> <p> </p> <p> </p>
VERITAS DL3 Event Data: Release v0.1 - Test Data Set
<p>The Very Energetic Radiation Imaging Telescope Array System (VERITAS; [1]) is a ground-based gamma-ray instrument at the Fred Lawrence Whipple Observatory in southern Arizona, USA. Comprising four 12m optical reflectors, VERITAS operates in the GeV-TeV energy range, with peak sensitivity between 100 GeV and 10 TeV.</p> <p>This repository contains high-level data products from VERITAS observations (2007-2024). The data includes event lists and instrument response functions processed using the Eventdisplay [2] package for calibration and reconstruction. Event lists support both point-like and full-enclosure analyses with five gamma-hadron separation cuts. Data follows the Gamma-ray Astronomy Data Format (GADF; [3]) and is compatible with open-source tools like gammapy [4].</p> <p>Access is currently restricted to VERITAS collaboration members, with future open access under discussion. Members should contact repository conveners for access.</p> <p>This is a test-release (v0.1) with data products not intended for scientific publication.</p> <p>References</p> <p>[1] VERITAS: https://veritas.sao.arizona.edu/<br>[2] Eventdisplay: an Analysis and Reconstruction Package for VERITAS [Computer software]. https://github.com/VERITAS-Observatory/EventDisplay_v4<br>[3] Data formats for gamma-ray astronomy. https://github.com/open-gamma-ray-astro/gamma-astro-data-formats<br>[4] gammapy: A python package for gamma-ray astronomy. https://github.com/gammapy/gammapy</p>
data set
Open the record for dataset details and reuse information.
Data set used in "FACIAL WRINKLE CATEGORIZATION USING CONVOLUTIONAL NEURAL NETWORK"
<p><span>For the purpose of training the neural network, a total of 5,098 images were provided, collected over a period of 3 years. These images were categorized into 4 classes, with the number of images in each category as evenly balanced as possible, with minimal deviation from the ideal distribution</span>. <span>A tool for the detection and classification of wrinkles is provided in this way.</span></p>
Seed retention data set
<p>Seed retention data set </p>
Magnetic properties of ultramafic rocks in the Troodos ophiolite, with compiled oxygen & hydrogen isotope data and magnetic susceptibility of serpentinites from different tectonic settings
Open the record for dataset details and reuse information.
Data set. Exploring the link between cation exchange capacity and magnetic susceptibility
Open the record for dataset details and reuse information.
FIGURE 1. Spectral analysis results for a hypothetical data set. Each bar represents a in Exploring character conflict in molecular data*
FIGURE 1. Spectral analysis results for a hypothetical data set. Each bar represents a different split in the tree. Bars above the x-axis represent the relative degree to which the data support that split. Bars below the x-axis represent the relative degree to which the data support relationships that conflict with (i.e. are incompatible with) that split. In this example, there is significant phylogenetic signal for relationships that conflict with splits 3, 5, 8 and 11.
Physical activity and RCI data sets
<p>Raw data from two studies on Lenten physical activity patterns</p>
Data set: Yearly RACMO2.3p2 variables, threshold temperature and Sentinel-2 melt pond volume
<p>Data set of yearly regional atmospheric climate model RACMO2.3p2 data over Antarctica. At the lateral and ocean boundaries the model is forced by ERA5 reanalysis data every 6 hours from 1979-2021. The model is run at 27 km horizontal resolution for the entire Antarctic ice sheet, which constitutes an update of the simulation forced from 1979-2018 by ERA-Interim reported in van Wessem et al., 2018. Upper air relaxation is also active.<br> To simulate the recent past (1950-2014) and the future (2015-2100) we use RACMO2.3p2 at 27 km resolution to dynamically downscale one historical and three future projections emission scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Detailed CESM2 description and latest updates are provided in Danabasoglu et., al 2020 and an evaluation over Greenland in Van Kampenhout et al., 2020.</p> <p>These data are then used to fit exponential and power-law relations of annual total liquid water production (melt + rain) and snow accumulation (snowfall - sublimation) to calculate MoA sensitivity as a function of annual average 2 m temperature. A comparison with Sentinel-2 melt pond observations can then be performed.</p> <p><strong>Data set includes: </strong></p> <p><strong>RACMO2.3p2-ERA5-3H</strong> - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 1979-2021 in mm w.e per year, and yearly average 2 m temperature in K, forced by 3 hourly ERA5 reanalysis data.</p> <p><strong>RACMO2.3p2-hist_r567</strong> - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 1950-2014 in mm w.e per year, and yearly average 2 m temperature in K, forced by 6 hourly CESM2 historical data.</p> <p><strong>RACMO2.3p2-SSP''126,245,585''_r567</strong> - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 2015-2100 in mm w.e per year, and yearly average 2 m temperature in K, forced by 6 hourly CESM2 future scenario (SSP1-2.6, SSP2-4.5, SSP5-8.5) data.</p> <p><strong>TT_ALL.nc </strong>- Antarctic threshold temperature <span class="math-tex">\(T_T\)</span> for MoA = 0.7 as described in the Methods section.</p> <p><strong>dT_ALL.nc </strong>- Uncertainty in Antarctic threshold temperature <span class="math-tex">\(T_T\)</span> for MoA = 0.7 as described in the Methods section.</p> <p><strong>TT_IS.nc </strong>- Antarctic threshold temperature <span class="math-tex">\(T_T\)</span> for MoA = 0.7 of 56 selected ice shelves as described in the Methods section.</p> <p><strong>dT_IS.nc </strong>- Uncertainty in Antarctic threshold temperature <span class="math-tex">\(T_T\)</span> for MoA = 0.7 of 56 selected ice shelves as described in the Methods section.</p> <p><strong>S2_meltpondvolume_v3.nc</strong> - Sentinel-2 melt pond volume as described in the Methods section.</p> <p><strong>Height_latlon_ANT27.nc </strong>- Grids of latitude, longitude, surface elevation (height), land/ice mask (mask2d), grounded land/ice mask (maskgrounded2d), aspect ratio, and surface slope.</p>
Discard data set
<p>N/A</p>
Common Knowledge Processing Patterns in Networks of Different Systems Minimal Data Set
<p>Common Knowledge Processing Patterns in Networks of Different Systems Minimal Data Set</p>
Data set networks for water protection
<p>The data set includes data collected with collaborative networks for water protection in Brazil.</p>
BIM and CAD Data sets for Large Scale Pilots
<p>Datasets for large-scale demonstration in the form digital plans including BIM are given in this object.</p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume2
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume1
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume6
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume4
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume5
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </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.