Skip to main content
Powered by ShareScore

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.

1,733

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

1,733 results for “Fatigue”

Learn how ShareScore rates datasets ↗
zenodo32/100

Fatigue Assessment Method for prestressed concrete sleeper

<p>The calculation of remaining fatigue life of concrete sleeper.</p>

opencc-by-4.0Dec 2016View details →
zenodo32/100

In-situ transilluminated white light imaging data of non-crimp fabric based fibre composite under fatigue loading

<p>In-situ transilluminated white light imaging data published with data in brief:&nbsp;</p> <p>Jespersen, K. M., Glud, J. A., Zangenberg, J., Hosoi, A., Kawada, H., &amp; Mikkelsen, L. P. (2018).&nbsp;Ex-situ X-ray computed tomography, tension clamp and in-situ transilluminated white light imaging data of non-crimp fabric based fibre composite under fatigue loading.<em> Data in Brief.</em></p> <p>as a part of the below journal paper.</p> <p>Jespersen, K. M., Glud, J. A., Zangenberg, J., Hosoi, A., Kawada, H., &amp; Mikkelsen, L. P. (2018). Uncovering the fatigue damage initiation and progression in uni-directional non-crimp fabric reinforced polyester composite. <em>Composites Part A.</em></p> <p>If using the data, please refer to one of the two.</p>

opencc-by-4.0Jan 2018View details →
zenodo32/100

Time-lapse helical X-ray computed tomography (CT) data of tensile fatigue damage in GFRP

<p>The X-ray CT data here is published&nbsp;with the paper - &nbsp;</p> <p>Wang, Y.; Mikkelsen, L.P.; Pyka, G.; Withers, P.J. Time-Lapse Helical X-ray Computed Tomography (CT) Study of Tensile Fatigue Damage Formation in Composites for Wind Turbine Blades.&nbsp;<em>Materials</em>&nbsp;<strong>2018</strong>,&nbsp;<em>11</em>, 2340.</p> <p>https://doi.org/10.3390/ma11112340</p> <p>More information about the data and the material can be found in the paper above.</p> <p>&nbsp;</p> <p>If using the data here, please cite the above paper.<em>&nbsp;</em></p> <p>Contact details for author: Ying Wang, ying.wang-4@manchester.ac.uk</p>

opencc-by-4.0Nov 2018View details →
zenodo32/100

Nondestructive Fatigue Life Prediction for Additively Manufactured Metal Parts through a Multimodal Transfer Learning Framework

Open the record for dataset details and reuse information.

opencc-by-4.0Aug 2024View details →
zenodo32/100

Fatigue crack initiation data for glass/epoxy notched composites (MOST-Spoke 11-WP6)

Open the record for dataset details and reuse information.

opencc-by-4.0Nov 2024View details →
zenodo32/100

Optimisation of RCA Content in Mortar Mixture Based on the Long-term Fracture and Fatigue Tests

<p>Data for the experimental study presented in: Optimisation of RCA Content in Mortar Mixture Based on the Long-term Fracture and Fatigue Tests</p>

restrictedcc-by-4.0Jul 2024View details →
zenodo32/100

Monte Carlo Simulations results for estimating an offshore structure fatigue life with a Fracture Mechanics based crack growth model, after additional information was considered through Bayesian inference at t=13 years

<p>Monte Carlo Simulations results for estimating an offshore structure fatigue life with a Fracture Mechanics based crack growth model, after additional information was considered through Bayesian inference at t=13 years</p>

opencc-by-4.0Dec 2018View details →
dryad32/100

Who develops pandemic fatigue? Insights from latent class analysis

<p>According to the World Health Organization, pandemic fatigue poses a serious threat for managing COVID-19. Pandemic fatigue is characterized by progressive decline in adherence to social distancing (SDIS) guidelines, and is thought to be associated with pandemic-related emotional burnout. Little is known about the nature of pandemic fatigue; for example, it is unclear who is most likely to develop pandemic fatigue. We sought to evaluate this issue based on data from 5,812 American and Canadian adults recruited during the second year of the COVID-19 pandemic. Past-year decline in adherence to SDIS had a categorical latent structure according to Latent Class Analysis, consisting of a group adherent to SDIS (Class 1: 92% of the sample) and a group reporting a progressive decline in adherence to SDIS (i.e., pandemic fatigue; Class 2: 8% of the sample). Class 2, compared to Class 1, was associated with greater pandemic-related burnout, pessimism, and apathy about the COVID-19 pandemic. They also tended to be younger, perceived themselves to be more affluent, tended to have greater levels of narcissism, entitlement, and gregariousness, and were more likely to report having been previously infected with SARSCOV2, which they regarded as an exaggerated threat. People in Class 2 also self-reported higher levels of pandemic-related stress, anxiety, and depression, and described making active efforts at coping with SDIS restrictions, which they perceived as unnecessary and stressful. People in Class 1 generally reported that they engaged in SDIS for the benefit of themselves and their community, although 35% of this class also feared they would be publicly shamed if they did not comply with SDIS guidelines. The findings suggest that pandemic fatigue affects a substantial minority of people and even many SDIS-adherent people experience emotionally adverse effects (i.e., fear of being shamed). Implications for the future of SDIS are discussed.</p>

opencc-zeroDec 2021View details →
zenodo32/100

Figure data for ``Fatigue crack growth under large scale yielding condition: a tool based on explicit crack growth''

<p>Figure data used for the paper &quot;Fatigue crack growth under large scale yielding condition: a tool based on explicit crack growth&quot; (doi 10.46298/jtcam.9296). The numerical values are provided as raw text in the tikz/pgfplots format. They can be compiled using latex/pdflatex engines. The name of each data file corresponds to the figure numbering in the paper.</p>

opencc-by-4.0Jan 2023View details →
zenodo32/100

DiscCoarse_Subvolumes_Porous_Fatigue_Viet_Tomo

<p>DiscCoarse_Subvolumes_Porous_Fatigue_Viet_Tomo</p>

opencc-by-4.0Apr 2023View details →
zenodo32/100

DiscFine_Subvolumes_Healthy_Fatigue_Viet_Tomo

<p>Contains, for 60 subvolumes (camemberts without any defects), nominal stress ranging from 100 to 140 MPa:</p> <p>a) stresses,</p> <p>b) volumes</p> <p><strong>Mesh type:</strong> Fine mesh</p> <p>Note: Summed volume of 20 subvolumes correctly equals the volume of experimental fatigue specimens used by Viet Duc Le.</p>

opencc-by-4.0Jun 2023View details →
zenodo32/100

DUO-GAIT: A Gait Dataset for Walking under Dual-Task and Fatigue Conditions with Inertial Measurement Units

<p>Details of the dataset are described&nbsp;in<a href="https://www.nature.com/articles/s41597-023-02391-w">&nbsp;this publication</a>.</p> <p>In recent years, there has been a growing interest to develop and evaluate gait analysis algorithms based on inertial measurement unit (IMU) data, which has important implications including sports, assessment of diseases, and rehabilitation. Multi-tasking and physical fatigue are two relevant aspects of daily life gait monitoring, but there is a lack of publicly available datasets to support the development and testing of methods using a mobile IMU setup. We present a dataset consisting of 6-minute walks under single- (only walking) and dual-task (walking while performing a cognitive task) conditions in non-fatigued and fatigued states from sixteen healthy adults. Especially, nine IMUs were placed on the head, chest, lower back, wrists, legs, and feet to record under each of the above-mentioned conditions. The dataset also includes a rich set of spatio-temporal gait parameters that capture the aspects of pace, symmetry, and variability, as well as additional study-related information to support further analysis. This dataset can serve as a foundation for future research on gait monitoring in free-living environments.</p> <p>&nbsp;</p> <p>----------</p> <p>Version History</p> <p>Version 3: Align the last few seconds of recording in raw data of sub_07, dual-task (this does not change any of the walking/exercise sensor signals or the rest of the dataset). Remove the&nbsp;.DS_Store files.</p> <p>Version 2: Update the license.</p> <p>Version 1: The original upload.</p>

openDec 2022View details →
zenodo32/100

The effects of two different fatigue protocols on movement quality during unanticipated change of direction in female soccer players (data file)

<p>This dataset contains the results of soccer players who participated in our study. In our study, we investigated the effects of two fatigue protocols on movement quality during change of direction in anticipated and unanticipated conditions.</p>

opencc-by-4.0Aug 2023View details →
zenodo32/100

DiscFine_Subvolumes_Porous_Fatigue_Viet_Tomo

<p>Contains, for 45 subvolumes (camemberts with defects), nominal stress ranging from 40 to 80 MPa:</p> <p>a) Neuber-corrected stresses,</p> <p>b) volumes</p> <p>c) cumulated plasticity in the 20th cycle (stabilized)</p> <p><strong>Mesh type:</strong> Fine mesh</p> <p>&nbsp;</p>

opencc-by-4.0Jun 2023View details →
zenodo32/100

Tearfilm and visual fatigue after smartphone use

<p>These data are the scores of tear film break-up time (BUT), binocular fusion maintenance (BFM), and subjective questionnaire before and after 30 minutes of smartphone use.</p><p>&nbsp;</p><p>BUT was measured by TSAS of RT7000.</p><p>BFM was measured with a self-made device.</p><p>The self-administered questionnaire is the one used in previous studies.</p><p>For the BFM and the questionnaire, please refer to previous studies of Hirota et al. (https://tvst.arvojournals.org/article.aspx?articleid=2676064).</p><p>&nbsp;</p><p>Thanks in advance for your favor.</p><p>Masakazu Hirota</p>

opencc-by-4.0Oct 2023View details →
ClinicalTrials.gov32/100

Fatigue Alleviation Through Neuromodulating Therapy in Multiple Sclerosis

ClinicalTrials.gov study NCT06569550. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Acupuncture or Self-Acupuncture in Managing Cancer-Related Fatigue in Women Who Have Received Chemotherapy for Stage I, Stage II, or Stage IIIA Breast Cancer

ClinicalTrials.gov study NCT00957112. IPD Sharing: Not stated. Countries: 1. Publications: 2.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Progressive Muscle Relaxation Exercises on Sleep, Fatigue and Pain in Pancreatic and Colon Cancer Patients

ClinicalTrials.gov study NCT06920082. IPD Sharing: NO. Countries: 1. Publications: 2.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Rhodiola Rosea for Mental and Physical Fatigue

ClinicalTrials.gov study NCT01278992. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

The Investigators Conducted a Study to Examine the Impact of Wild Ginseng Extract (WG) on Exercise Performance, Cognitive Function, and Fatigue Recovery Among Twelve Healthy Adult Males

ClinicalTrials.gov study NCT06679725. IPD Sharing: NO. Countries: 1. Publications: 12.

closedIPD-NOFeb 2026View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record