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3,481 results for “data set”
Over and Under Sampled Data-sets of Code Issues in Java Open-Source Projects
<p>The dataset comprises code changes made to 15 Java Open-Source projects, classified with sentiment values (0 for negative and 1 for positive) based on developer reviews during various revision submissions. The dataset is available in 8 versions, each containing a sampled dataset using an over or under-sampling technique.</p>
Global reference data set for validating ESA WorldCereal temporary cropland extent
<p>IIASA team has created a new validation data set, which is completely independent from all other existing maps or reference data sets, and which is in line with the cropland definitions and mapping period of the WorldCereal products. To decide if this is an active cropland in each period, the experts looked at very high-resolution Google historical imagery and Google Street level images, Microsoft Bing images, ESRI imagery, Planet historical data, Sentinel-2 time series, and Modis NDVI time series. The experts were asked to label 5 by 5 Sentinel pixels (each pixel 10m by 10m) either as winter crops, or as summer crops, or as maize (if this was possible), or as active crops (where it was not possible to confirm a growing season, e.g. overlap between seasons was too big or crop fields were too small in size), or as no crops, or as not sure where was too little information available for 2021. There was additional question on irrigation system, either circle, or other irrigation, or rainfed, or not sure. </p> <p>Fields:</p> <p>"rowid" -unique row identifier</p> <p>"submissionid" – unique submission id, which consists of 25 single pixels (rows)</p> <p>"timestamp" – time stamp of each submission</p> <p>"sampleid" – unique sample site, which could have a few submission ids</p> <p>"submission_itemid" – unique single pixel submission id</p> <p>"enhancement" – unique legend identifier in the Geo-Wiki database</p> <p>"question" – question asked (either on crop presence or irrigation)</p> <p>"answer" – answer to a question asked</p> <p>"sub_pixel_x","sub_pixel_y" – centroids of a single pixel in WGS84</p>
FIRST PRINCIPLE DESIGN LOAD ESTIMATION FOR LH2 FUEL TANKS BY MEANS OF 0D APPROACH - OMAE Data Set
<p>Supplementary data set for the OMAE publication "FIRST PRINCIPLE DESIGN LOAD ESTIMATION FOR LH2 FUEL TANKS BY MEANS OF 0D APPROACH". Contains the complete set of data for the presented cases while only selected data series are shown in the paper.</p>
BIOHARV project INTERREG V - Piezoelectric biobased polymers - Data set n°2
<p>The BIOHARV projet is financed by FEDER, Wallonia Region, West-Vlaanderen Region and Agentshap Innoveren & Ondernemen. BIOHARV project started on 2016, October 1st for 4 years. Six academic & technological partners are gathered (Institute Mines Telecom North Europe, Armines, University of Mons, Centexbel, University of Lille and Polytechnic University Hauts-De-France. The main objective of the BIOHARV project is demonstrate & investigate piezoelectric, electroactive & electromechanical properties of biobased polymers. </p> <p><strong>This dataset includes the physico-cheminal properties for various types of PLA processed by extrusion-MDO (machine-direction orientation) in relation to their shear piezoelectric properties. Various characterization techniques are used such as DSC, (2D-)WAXS, (2D-)SAXS and FTIR (non polarized and polarized). The related article "Shear Piezoelectricity of Poly(L-Lactide) Films Manufactured by Extrusion – Orientation: An Insight on Process – Structure – Properties Relationships" will be published soon.</strong></p>
Data set: The opening dynamics of the lateral gate regulates the activity of rhomboid proteases
<p>Dataset:</p> <p><strong>The opening dynamics of the lateral gate regulates the activity of rhomboid proteases</strong></p> <p>Input: MD simulations + docking results</p>
Data set: genetic variants related to SARS-CoV-2 viremia
<p>Data set generated to evaluate the association between SNPs from genes related to SARS-CoV-2 pathogenesis and the presence of viremia.</p>
D2.1 - Demonstrator baseline and market characteristics report - Consumer survey data set
<p>This is the data set for D2.1 "Demonstrator baseline and market characteristics report" defining the current baseline and the target/improved circular business models for two demonstrators and analyzing both demonstrators´ market characteristics and their impact on the target circular business models.</p> <p> </p>
D6.6 - White goods pilot report - LCA Data set
<p>This is the data set used for the LCA of a pay-per-wash washing machine from Gorenje. The LCA compares the pay-per-wash washing machine to a washing machine that is sold in a traditional way.</p>
Data set related to the manuscript "Investigating particle size effects on NMR spectra of ions diffusing in porous carbons through a mesoscopic model"
<p>Graphical files in the agr format for all the figures in the manuscript entitled "Investigating particle size effects on NMR spectra of ions diffusing in porous carbons through a mesoscopic model". Examples of input files for the lattice simulations are also provided.</p>
Chapter 11 Image set for the book, "Data Science for Nano Image Analysis"
<p>This is the image set used in Chapter 11 of the book, "Data Science for Nano Image Analysis".</p>
Chapter 6 Image set for the book, "Data Science for Nano Image Analysis"
<p>This is the image set used in Chapter 6 of the book, "Data Science for Nano Image Analysis"</p>
Chapter 5 Image set for the book, "Data Science for Nano Image Analysis"
<p>This is the image set used in Chapter 5 of the book, "Data Science for Nano Image Analysis".</p>
Chapter 8 Image set for the book, "Data Science for Nano Image Analysis"
<p>This is the image set used in Chapter 8 of the book, "Data Science for Nano Image Analysis".</p>
Chapter 4 Image set for the book, "Data Science for Nano Image Analysis"
<p>This is the image set used in Chapter 4 of the book, "Data Science for Nano Image Analysis".</p>
Chapter 3 Image set for the book, "Data Science for Nano Image Analysis"
<p>This is the image set used in Chapter 3 of the book, "Data Science for Nano Image Analysis".</p>
Chapter 7 Image set for the book, "Data Science for Nano Image Analysis"
<p>This is the image set used in Chapter 7 of the book, "Data Science for Nano Image Analysis".</p>
Chapter 10 Image set for the book, "Data Science for Nano Image Analysis"
<p><br> This is the image set used in Chapter 10 of the book, "Data Science for Nano Image Analysis".</p>
Software Requirements Data Set
<p>For automatic software requirements specification (SRS) processing and quality evaluation, we have collected textual requirements from four different sources:</p> <ul> <li>a set of requirements from the PUblic REquirements (PURE) dataset (folders prefixed with upper case 'P') [<a href="https://zenodo.org/record/7118517">https://zenodo.org/record/7118517</a>],</li> <li>a set of requirements collected by Hayes et al. (folders prefixed with upper case 'H') [<a href="https://doi.org/10.1109/REW.2019.00052">https://doi.org/10.1109/REW.2019.00052</a>],</li> <li>a set of requirements provided by Dalpiaz (folders prefixed with lower case 'g') [<a href="https://doi.org/10.1016/j.infsof.2018.12.007">https://doi.org/10.1016/j.infsof.2018.12.007</a>],</li> <li>a custom collection of requirements found in the Internet (folders prefixed with upper case 'C').<br> </li> </ul> <p>We preserve the original file of the requirements (TXT, PDF, RTF, DOC or HTML) and add a plain text conversion (files called <code>_Raw.txt</code>) or, for some of them, Markdown form (files called <code>_Raw.md</code>). For some of them, we have extracted part of functional requirements (files called <code>FunctionalRequirements</code>) or functional specification relevant parts (files called<code> AllRelevant)</code>.</p>
Data Set: Uncertainty
<p>Dataset of the measurements presented in the futureEnergy D8 submission</p>
Potato Leaf data set
<p>A Collection of potato images. Some with manual annotation of leaf areas in .json format. Some with physically measured leaf area and leaf biomass measurements contained in the csv file.</p> <p>pot_data_withimgnames_fullset.csv contains information about which plants correspond to which images and the physical ground truth data. </p> <p>Full details of data gathering can be seen in paper <a href="https://arxiv.org/abs/2305.09418">here</a>. Please cite the paper if you use our 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.