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.
5,738
datasets available to search
ShareScore release 0.9.0
Dataset results
5,738 results for “Standards”
Using a standardized sound set to help characterize misophonia: The international affective digitized sounds
<p>Misophonia is a condition characterized by negative affect, intolerance, and functional impairment in response to particular repetitive sounds usually made by others (e.g., chewing, sniffing, pen tapping) and associated stimuli. To date, researchers have largely studied misophonia using self-report measures. As the field is quickly expanding, assessment approaches need to advance to include more objective measures capable of differentiating those with and without misophonia. Although several studies have used sounds as experimental stimuli, few have used standardized stimuli sets with demonstrated reliability or validity. To conduct rigorous research to better understand misophonia, it is important to have an easily accessible, standardized set of acoustic stimuli for use across studies. Accordingly, in the present study, the International Affective Digitized Sounds (IADS-2), developed by Bradley and Lang [1], were used to determine whether participants with misophonia responded to certain standardized sounds differently than a control group. Participants were 377 adults (132 participants with misophonia and 245 controls) recruited from an online platform to complete several questionnaires and respond to four probes (arousal, valence, similarity to personally relevant aversive sounds, and sound avoidance) in response to normed pleasant, unpleasant, and neutral IADS-2 sounds. Findings indicated that compared to controls, participants with high misophonia symptoms rated pleasant and neutral sounds as significantly more (a) arousing and similar to trigger sounds in their everyday life, (b) unpleasant, and (c) likely to be avoided in everyday life. For future scientific and clinical innovation, we include a ranked list of IADS-2 stimuli differentiating responses in those with and without misophonia, which we call the IADS-M.</p>
Aligning Data Management Plans with Community Standards using FAIR Implementation Profiles
<p>Here you can find the files corresponding to our submission titled 'Aligning DMPs with Community Standards using FIPs'.</p> <p>- VU DMP template and the mapping is included in the folder /VU-DMP-template-and-mapping</p> <p>- All the FAIR Implementation Profiles are included in the folder /FIPs.</p> <p>- The knowledge model we created for the project, and a small demo of the interface are in the folder /KM-and-demo.</p> <p>- The folder /user-study consists of the following:</p> <p> a) The mock DMPs we provided to the participants of this research are in /mock_DMPs.</p> <p> b) We downloaded the resulting DMPs after participants completed their DMPs, they are in the folder /resulting_DMPs.</p> <p> c) Survey results can be found in the folder /survey_results.</p> <p> d) Some Python scripts were used for the analysis of the survey results. They are in the folder /Python_script_for_analysis.</p> <p><br>The project is open source under the license CC-BY 4.0.</p> <p>Contact: Shuai Wang (shuai.wang@vu.nl)</p> <p> </p>
Evaluation of comparative Efficacy of two routes of administration of Carathmus Tinctorius (Medicated Enema and Nasal Administration) as an Adjuvant Therapy with Standard Care With Physiotherapy in the Rehabilitation of Thrombolytic Stroke (Pakshaghat): A Randomized Controlled Trial Protocol
Open the record for dataset details and reuse information.
Figure 1 in Guidelines and quantitative standards to improve consistency in cetacean subspecies and species delimitation relying on molecular genetic data
Figure 1. Guidelines for studies of cetacean taxonomy based on genetic data.
Challenges in adjusting scoring matrices when comparing functional motifs with non-standard compositions
<p>This research was funded by the National Science Centre in Poland (grant number 2021/41/N/ST6/01919)</p>
Inference products and plotting code for "Some Times in Standard Cosmology"
<p>This zip file contains the Monte Carlo Markov chains (MCMC), the plotting codes, and the figures for the paper "Some Times in Standard Cosmology" by Lukas Tobias Hergt and Douglas Scott (<a href="https://arxiv.org/abs/2411.07703">arXiv:2411.07703</a>):</p> <ul> <li>The folder <code>MCMC__LCDM__PR3_lowlTT_PR4_LoLLiPoP-lowlEE_HiLLiPoP-TTTEEE_lensing</code> contains the MCMC run generated with Cobaya. For details about theoretical model, input parameters, and likelihoods refer to the <code>.yaml</code> files therein or to information in the corresponding paper.</li> <li>The <code>some_times_in_standard_cosmology.py</code> file was used for the post-processing of the MCMC chains; specifically, to compute the physical times, which are not standard derived parameters.</li> <li>The <code>some_times_in_standard_cosmology.ipynb</code> file contains the plotting code and the <code>some_times_in_standard_cosmology_sympy.ipynb</code> file contains derivations of the 2-fluid solutions. We additinally provide the <code>some_times_in_standard_cosmology.html</code> and <code>some_times_in_standard_cosmology_sympy.html</code> files to allow for easy read access via a browser.</li> <li>The PDF files <code>some_times_in_standard_cosmology.pdf</code> and <code>some_times_in_standard_cosmology_2d.pdf</code> are the two figures published in the paper.</li> <li>The <code>.tex</code> files contain the data used for the tables in the paper.</li> </ul>
Standard methods for dissection of Varroa destructor females supplementary videos
<p>These three videos present methodological steps to perform Varroa destructor females dissection either ventrally (Video S1) or dorsally (Video S2 and S3)</p>
Dataset: Improving the prediction of fertilizer phosphorus availability to plants with simple, but non-standardized extraction techniques
<p>Dataset: Improving the prediction of fertilizer phosphorus availability to plants with simple, but non-standardized extraction techniques</p>
Lock-in and Standard DPC raw images associated to publication 10.1364/PRJ.445896
<p>Raw images obtained with helicam C3 in a DPC microscope setup. The raw images were used for the figures in the publication Chiara Bonati, Damien Loterie, Timothé Laforest, Christophe Moser. Lock-in incoherent differential phase contrast imaging. Photonics Research, 2022, 10(1):237.</p> <p>Contents of the data set:</p> <ol> <li><strong>Contrast comparison</strong>: images used for Figure 4. Several USAF targets of different height, introducing varying phase differences. Samples were imaged under both standard and lock-in DPC. <ol> <li><strong>Lock-in DPC</strong>: lock-in DPC image sets. Each image was collected over four cycles of 140 us each. <ol> <li><strong>5_mrad</strong>: 5 mrad sample <ul> <li><strong>Background</strong>: no sample image <ul> <li><strong>I</strong>: Frame I</li> <li><strong>Q</strong>: Frame Q</li> </ul> </li> <li><strong>Sample</strong>: sample image <ul> <li><strong>I</strong>: Frame I</li> <li><strong>Q</strong>: Frame Q</li> </ul> </li> </ul> </li> <li><strong>13dot8_mrad</strong>: 13.8 mrad sample</li> <li><strong>15dot1_mrad</strong>: 15.1 mrad sample</li> <li><strong>18dot9_mrad</strong>: 18.9 mrad sample</li> <li><strong>35dot2_mrad</strong>: 35.2 mrad sample</li> <li><strong>50dot5_mrad</strong>: 50.5 mrad sample</li> </ol> </li> <li><strong>Standard DPC: </strong>Same set of images, under standard DPC conditions. Each illumination (left and right) was recorded for 1 us. <ol> <li><strong>5_mrad</strong>: 5 mrad sample <ul> <li><strong>Background</strong>: no sample image <ul> <li><strong>L</strong>: Image under left illumination</li> <li><strong>R</strong>: Image under right illumination</li> </ul> </li> <li><strong>Sample</strong>: sample image <ul> <li><strong>L</strong>: Image under left illumination</li> <li><strong>R</strong>: Image under right illumination</li> </ul> </li> </ul> </li> <li><strong>13dot8_mrad</strong>: 13.8 mrad sample</li> <li><strong>15dot1_mrad</strong>: 15.1 mrad sample</li> <li><strong>18dot9_mrad</strong>: 18.9 mrad sample</li> <li><strong>35dot2_mrad</strong>: 35.2 mrad sample</li> <li><strong>50dot5_mrad</strong>: 50.5 mrad sample</li> </ol> </li> </ol> </li> <li><strong>Reconstruction</strong>: Image sets used for figures 5 and 6 <ol> <li><strong>USAF_50dot5mrad</strong>: Image sets of a 50.5 mrad glass USAF target. <ol> <li><strong>Illumination</strong>: Folder containing the back-focal plane characterisation of the imaging system, used to compute the transfer functions for phase reconstruction. <ul> <li>BFP: the back-focal plane aperture of the 0.4 NA objective</li> <li>P_1: reduced pupil used in the experiments</li> <li>s_L: left source</li> <li>s_R: right source</li> </ul> </li> <li><strong>Lock-in DPC</strong>: lock-in DPC image set. The equivalent exposure time was 464 us.</li> <li><strong>Standard DPC</strong>: standard DPC image set. Each illumination was exposed for 8 us.</li> </ol> </li> <li><strong>Onion</strong>: Image sets of onion epidermal cells. <ol> <li><strong>Lock-in DPC</strong>: lock-in DPC images for varying equivalent exposure times. <ul> <li>104 us</li> <li>120 us</li> <li>136 us</li> <li>152 us</li> <li>168 us</li> <li>184 us</li> <li>200 us</li> <li>216 us</li> <li>232 us</li> <li>248 us</li> </ul> </li> <li><strong>Standard DPC</strong>: Standard DPC image set at 7 us exposure time</li> </ol> </li> </ol> </li> </ol> <p> </p> <p> </p>
Stocks data of Stocks in the German Prime Standard 2018
<p>Data was used in publication:</p> <p>Thrun, M. C.: Exploiting Distance-Based Structures in Data Using an Explainable AI for Stock Picking, Information, MDPI, 2022.</p> <p>Using this data please cite the publication.</p>
ECCO v4 standard analysis sample (v4r3)
<p>Generated from the ECCO output (version 4, release 3) available to download from <a href="https://ecco-group.org/products.htm">ecco-group.org</a> using a Julia workflow available from <a href="https://github.com/gaelforget/OceanStateEstimation.jl">OceanStateEstimation.jl</a> (see <a href="https://gaelforget.github.io/OceanStateEstimation.jl/dev/">the docs</a>).</p>
ECCO v4 standard analysis sample
<p>Generated from the ECCO output (version 4, release 2) available to download from <a href="https://ecco-group.org/products.htm">ecco-group.org</a> using a Julia workflow available from <a href="https://github.com/gaelforget/OceanStateEstimation.jl">OceanStateEstimation.jl</a> (see <a href="https://gaelforget.github.io/OceanStateEstimation.jl/dev/">the docs</a>).</p> <p>The ECCO output (version 4, release 2) used here is archived @ <a href="https://doi.org/10.7910/DVN/NXYKDW">https://doi.org/10.7910/DVN/NXYKDW</a></p>
ECCO v4 standard analysis sample (v4r4)
<p>Generated from the ECCO output (version 4, release 4) available to download from <a href="https://ecco-group.org/products.htm">ecco-group.org</a> using a Julia workflow available from <a href="https://github.com/gaelforget/OceanStateEstimation.jl">OceanStateEstimation.jl</a> (see <a href="https://gaelforget.github.io/OceanStateEstimation.jl/dev/">the docs</a>).</p> <p> </p>
Individual glass and secondary standard analyses for tephra described in sediment cores from Skilak Lake, Alaska
<p>This dataset comprises individual glass shard and secondary standard analyses for tephra collected in sediment cores from Skilak Lake, Alaska. These geochemical analyses were used in the research article in Sedimentology titled “Unravelling a 2300 year long sedimentary record of megathrust and intraslab earthquakes in proglacial Skilak Lake, south-central Alaska” by Praet et al. (2022). DOI: <a href="https://doi.org/10.1111/sed.12986">10.1111/sed.12986</a></p>
Repository for "Standardized classification of cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography"
<p>Repositories for "Standardized classification of cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography"</p> <p>Repository 1: Digital subtraction angiographies of CVS patients for grading with pM1 values</p> <p>Repository 2: Vessel values</p> <p>Repository 3: Clinical data of CVS patients</p>
Photos of participants of Turin Workshop (11 and 12 April 2022): Skull collections. Series, standardization and instruments
<p>During the two days of the workshop in the Museum of Human Anatomy was inaugurated the Exhibition: "The art of trepanning".</p> <p>The artworks of the Peruvian artist Fernando Bedoya, exhibited near the showcase where the two South American mummies are preserved, are intended to dialogue with the human findings as well as evoking the ancient surgical practices of the Incas, known as trepanation, which consisted of the perforation of the skull.</p> <p>Bedoya, through his ceramic replicas of ancient heads, imitates the act of trepanation by perforating twice the head. One hole is left open, following the sign of the surgical intervention, while the other hole is covered with a bottle cap of Coca-Cola, a brand of the modern global exploiter.</p> <p>On display are also four of his engravings from the “Fardos” series, where the use of collage and silkscreen techniques bind together like the bandaging of a mummy.</p>
Republication package for: "Publishing while female: Are women held to higher standards? Evidence from peer review"
<p>Replication package to reproduce all tables and figures in the paper "Publishing while female: Are women held to higher standards? Evidence from peer review"</p>
Data from: Encoding laboratory testing data: case studies of the national implementation of HHS requirements and related standards in five laboratories
<p><strong>Objective</strong>: Assess the effectiveness of providing Logical Observation Identifiers Names and Codes (LOINC®)-to-In Vitro Diagnostic (LIVD) coding specification, required by the United States Department of Health and Human Services for SARS-CoV-2 reporting, in medical center laboratories and utilize findings to inform future United States Food and Drug Administration policy on the use of real-world evidence in regulatory decisions.</p> <p><strong>Materials and Methods</strong>: We compared gaps and similarities between diagnostic test manufacturers' recommended LOINC® codes and the LOINC® codes used in medical center laboratories for the same tests.</p> <p><strong>Results</strong>: Five medical centers and three test manufacturers extracted data from laboratory information systems (LIS) for prioritized tests of interest. The data submission ranged from 74 to 532 LOINC® codes per site. Three test manufacturers submitted 15 LIVD catalogs representing 26 distinct devices, 6956 tests, and 686 LOINC® codes. We identified mismatches in how medical centers use LOINC® to encode laboratory tests compared to how test manufacturers encode the same laboratory tests. Of 331 tests available in the LIVD files, 136 (41%) were represented by a mismatched LOINC® code by the medical centers (chi-square 45.0, 4 df, P &lt; .0001).</p> <p><strong>Discussion</strong>: The five medical centers and three test manufacturers vary in how they organize, categorize, and store LIS catalog information. This variation impacts data quality and interoperability. </p> <p><strong>Conclusion</strong>: The results of the study indicate that providing the LIVD mappings was not sufficient to support laboratory data interoperability. National implementation of LIVD and further efforts to promote laboratory interoperability will require a more comprehensive effort and continuing evaluation and quality control.</p>
BiodivNERE: Gold Standard Corpora for Named Entity Recognition and Relation Extraction in Biodiversity Domain
<p>BiodivNER+RE are two gold-standard manually annotated corpora that are meant to be for Named Entity Recognition (NER) and Relation Extraction (RE) tasks based on abstracts and metadata files from the biodiversity domain</p> <p>Such corpora are designed for machine learning techniques, for example, NER as TokenClassification technique, and RE as SequenceClassification technique.</p>
Grape V1 Data: Frequency Estimation and Amplitudes of North American Time Standard Stations
<p>Frequency and amplitude estimation data collected by Grape V1 stations in the Personal Space Weather Station network. </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.