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.
1,045
datasets available to search
ShareScore release 0.9.0
Dataset results
1,045 results for “Generated Data”
ViSAPy-generated test data from Lee JH., et al. Advances in Neural Information Processing Systems 30 (NIPS 2017), pp4002--4012
<p>This dataset corresponds to the simulated test data for spike-sorting algorithms in Figure 3 of:</p> <p>Lee, Jin Hyung and Carlson, David E and Shokri Razaghi, Hooshmand and Yao, Weichi and Goetz, Georges A and Hagen, Espen and Batty, Eleanor and Chichilnisky, E.J. and Einevoll, Gaute T. and Paninski, Liam. YASS: Yet Another Spike Sorter. Advances in Neural Information Processing Systems 30 (NIPS 2017). Editors I. Guyon and U. V. Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett, year 2017, pp4002-4012.<br> publisher: Curran Associates, Inc. URL http://papers.nips.cc/paper/6989-yass-yet-another-spike-sorter.pdf</p>
Extended data for the paper "Reliable generation of native-like decoys limits predictive ability in fragment-based protein structure prediction"
<p>Extended data for the paper:<br> Reliable generation of native-like decoys limits predictive ability in fragment-based protein structure prediction</p> <p>Authors:<br> Shaun M Kandathil, Mario Garza-Fabre, Simon C Lovell and Julia Handl</p> <p>--------------------------------</p> <p>Contents of the zip file:</p> <p> </p> <p>Directory 'ECDFplots':<br> ----------------------<br> Data corresponding to Figure 3 for all targets, for the bilevel and ILS protocols. Data are available following stages 3 and 4 of the low-resolution protocol.</p> <p>Directory 'ScoreRMSDplots_3archivers':<br> --------------------------------------<br> Data corresponding to Figures 6 and 9 for all targets. Data corresponding to decoys obtained after low-resolution stages 3 and 4 can be found in subdirectories 'Stage3' and 'Stage4', respectively.<br> </p>
Data sets for " The nature of mean-field generation in three classes of optimal dynamos"
<pre>The tar archive Optimal_Dynamos.tar contains and index.html file with links to the run directories for each figure and the two tables of the paper "The nature of mean-field generation in three classes of optimal dynamos" by Axel Brandenburg (Nordita) and Long Chen (Durham University) with the temporary URL http://norlx51.nordita.org/~brandenb/tmp/long_chen. Corrections and updates are available on the active URL to this tar archive: https://www.nordita.org/~brandenb/projects/Optimal_Dynamos/</pre>
Logistics Transport Label Data - 'Lean Training Data Generation for Planar Object Detection Models in Unsteady Logistics Contexts'
<p>Example dataset described in ICMLA2019 Paper 'Lean Training Data Generation for Planar Object Detection Models in Unsteady Logistics Contexts' (Dörr, Brandt, Meyer, Pouls).</p>
EEG data for generating reference rdFC patterns and sample rdFC patterns
<p>The correlation structure embedded in scalp EEG data is explored through three representative reference rdFC patterns which can be generated from the data in referenceEEG.txt. Three sample EEG data files, each of a triplet of electrodes, serve as examples for comparison with the reference rdFC patterns.</p>
Evaluation data used in "An innovative STEM outreach model (OH-Kids) to foster the next generation of geoscientists, engineers, and technologists"
<p>This repository contains all data of the evaluation questionnaire used to assess modifications in pupils’ perceptions of same water resources concepts and science and scientist resulting from the application of OH-Kids outreach model in six Mexican primary schools (n=344 pupils).</p>
Data for figures in the article "Thermal-integration in Photoelectrochemistry for Fuel and Heat Co-Generation"
<p>This repository contains the data used to generate figures in the article "<span>Thermal-integration in Photoelectrochemistry for Fuel a</span><span>nd Heat Co-Generation" in 2024 in Sustainable Energy and Fuels.</span></p> <p><span>Authors of this data and the article are Evan F Johnson and Sophia Haussener.</span></p>
Precipitation hydrogen isoscape for East China from 1969 to 2017 generated based on data fusion of iGCMs simulations
<p>The dataset includes the stable hydrogen isotope of precipitation for East China over the 1969-2017 period, at a spatial resolution of 50-60 km and a monthly temporal resolution. This dataset was built based on the Convolutional Neural Network (CNN) method, fusing observations and isotope-equipped general circulation models (iGCMs) simulations of hydrogen isotope composition. Some physical-based ancillary data are also introduced in the fusion methods, including elevation and meteorological data, to enrich the climate and terrain information in the process of data fusion.</p>
Source Data for the paper: "Quantum-classical simulations reveal the photoisomerization mechanism of a prototypical first-generation molecular motor"
<p>This dataset contains the raw data for the results shown in the paper.</p> <p>For each figure of the paper (main text), one directory with data file(s) is provided.</p>
Data for publication: 'Publication Patterns in the Humanities: Generational Shifts and Changing Research Agendas'
<p>This repository contains data supporting the paper <em>Publication Patterns in the Humanities: Generational Shifts and Changing Research Agendas</em>. The study analyzes the publication behaviors of approximately 60,000 humanities scholars from Spanish-speaking countries, focusing on generational shifts and research topic trends. Due to copyright restrictions from Dialnet, raw data used in the study cannot be publicly shared.</p> <p>Included files:</p> <ul> <li><strong>archetypes_summary.csv</strong> - Percentiles of archetype attributes by research fields and their labels after clustering.</li> <li><strong>authors_metrics_dialnet.tsv</strong> - Aggregated metrics for 60,063 authors from Dialnet used to build archetypes (anonymized data).</li> <li><strong>basemap_network.json</strong> - Basemap of the thematic landscape.</li> <li><strong>topic_descriptions.tsv</strong> - Titles and descriptions of the 1437 research topics.</li> </ul>
Training data for "PepINVENT: Generative peptide design beyond the natural amino acids"
<p>The zipped file contains the training and the validation data used to train the PepINVENT model.</p>
The ECOLOPES Voxel Model: Multi-domain data integration for ontology-aided generative computational design of ecological building envelopes
<p>The research portrayed in this article is part of the research project ‘ECOlogical building enveLOPES: a game-changing design approach for regenerative ecosystems’ funded by Horizon 2020 Future and Emerging Technologies. The overall research project focuses on developing a multi-domain data-driven computational design framework for the design of ecological building enclosures that addresses humans, plants, animals and microbiota. This article focuses on the development of a key component of the computational workflow in which initial designs are computationally initiated generated and analyzed, namely the ECOLOPES Voxel Model that contains and correlates multi-domain spatialised data for the design process, and its interactions with other components of the ontology-aided generative computational design process for ecological building envelopes.</p> <p>This repository contains all relevant data produced in this paper. Extended technical description is available in the Appendix A to the published paper, containing listing and description of individual voxel data layers. Data were exported from the RDB server (PostgreSQL) in text-based, future-proof format (csv).</p>
Data for Quantifying the Impact of Parametric Uncertainty on Automatic Mechanism Generation for CO2 Hydrogenation on Ni(111)
<p>Data, scripts, and all generated mechanisms for the preprint and article "Quantifying the Impact of Parametric Uncertainty on Automatic Mechanism Generation for CO<sub>2</sub> Hydrogenation on Ni(111)"</p>
Generation of transcriptional novelty by transposable element insertions in Arabidopsis, RNAseq Control Condition Sequencing Data
<p><strong>Arabidopsis stranded 150 bp paired end RNA sequencing data (Illumina) of plants that were grown under control conditions for the manuscript "Generation of transcriptional novelty by transposable element insertions in Arabidopsis"</strong></p> <p><strong><strong>Plant growth conditions</strong></strong></p> <p>Sequenced F4 seeds were sterilized for 10 minutes in 10% bleach, rinsed, and stratified at 4°C for four days in the dark before being sown on 0.5x Murashige & Skoog media (Du<em>schefa cat# M0222</em>) and transferred to growth chambers under long day conditions (16h of light at 24°C followed by 8h of darkness at 21°C; 20 seeds per plate, 6 replicate plates). Ten days after sowing, plants were subjected to 6°C for 24 hours and control plants were returned to normal long day growing conditions for 24 hours before harvesting (3 replicate plates per condition).</p> <p><strong><strong>RNA extraction and sequencing</strong></strong></p> <p>Seedlings were harvested and RNA extractions were done on pools of 5 plants. RNA extractions were performed for 3 biological replicate samples for each line in each condition (n=96) using the Macherey-Nagel NucleoSpin RNA kit (cat# 740955.50). Samples were sent to Novogene for Illumina 150bp paired-end sequencing using a stranded poly-A library.</p> <p><strong>RNAseq sample descriptions of the plants grown under control conditions</strong></p> <p>wt_control: wild-type plants.</p> <p>wtHS_control: wild-type plants that have been submitted to heat stress in a previous generation.</p> <p>wtAZ_control: wild-type plants that have been submitted to epigenetic drug treatments (alpha-amanitin and zebularine) in a previous generation.</p> <p>htLine#: plants carrying additional <em>ONSEN</em> transposable element insertions.</p> <p>Files description: Forward and reverse strand RNA seq data are combined in one file. The numbering at the end ("_1") denominates the biological replicate number.</p>
Opinions and data on short food supply chains related policy analysis in 9 EU countries generated in the H2020 SMARTCHAIN Project grant number: 773785
<p>Questionnaires: Opinions and data on short food supply chains related policy analysis in 9 EU countries generated in the H2020 SMARTCHAIN Project grant number: <strong>773785</strong></p>
Biomedical Data-to-Text Generation via Fine-Tuning Transformers
<p>Biomedical Dataset (”BioLeaflets”) for the paper "Biomedical Data2Text Generation via fine-tuning transformers" (INLG'21)</p>
SASC: A Simple Approach to Synthetic Cohorts. Applying COVID-19 clinical data to generate longitudinal observational patient cohorts and comparison with alternative synthetic cohort approaches as well as real patient data
<p>Subset from COVID-19 Dataset from https://zenodo.org/record/3766350#.YVcfyTFBxgA. Used as reference for a publication dealing with synthetic patient cohort generation.</p>
Populations of local direction-selective cells encode global motion patterns generated by self-motion. Data, Code and Model.
<p>Directional tuning of the population of local motion detectors T4/T5 in the visual system of the fruit fly <em>Drosophila melanogaster</em>. Direction tuning and receptive field location was measured by recording responses to visual stimuli containing dark or bright edges/stripes moving into 8 directions. All provided MATLAB scripts were used to analyze and illustrate data show in the manuscript 'Populations of local direction-selective cells encode global motion patterns generated by self-motion.'</p> <p>All data were obtained using <em>in vivo </em>two photon microscopy. Image time series were preprocessed using SIMA python software for motion alignment and further processed using custom written matlab or python code.</p> <p>Please find all relevant information to use the code in the README file.</p>
Data - Co-feeding of VGO and pine-wood derived hydrogenated pyrolysis oils in an Fluid Catalytic Cracking pilot plant to generate olefins and gasoline
<p>Dataset to the corresponding research article with the same title. Research article is submitted to the open research europe platform.</p>
Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data
<p>Files uploaded here are related to the paper titled "Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data". Here we investigate how generative adversarial networks can be used to match simulated- and experimental INS 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.