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.
842
datasets available to search
ShareScore release 0.9.0
Dataset results
842 results for “Smartphone”
Data from: Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis
Objective: The number of mobile applications addressing health topics is increasing. Whether these apps underwent scientific evaluation is unclear. We comprehensively assessed papers investigating the diagnostic value of available diagnostic health applications using in-built smartphone-sensors. Methods: Systematic Review - Medline, Scopus, Web of Science inclusive Medical Informatics and Business Source Premier (by citation of reference) were searched from inception until December 15th, 2016. Checking of reference lists of review articles and of included articles complemented electronic searches. We included all studies investigating a health application that used in-built sensors of a smartphone for diagnosis of disease. The methodological quality of 11 studies used in an exploratory meta-analysis was assessed with the QUADAS-2 tool and the reporting quality with the STARD statement. Sensitivity and specificity of studies reporting two-by-two tables were calculated and summarized. Results We screened 3'296 references for eligibility. Eleven studies, most of them assessing melanoma screening apps, reported 17 two-by-two tables. Quality assessment revealed high risk of bias in all studies. Included papers studied 1'048 subjects (758 with the target conditions and 290 healthy volunteers). Overall, the summary estimate for sensitivity was 0.82 (95 % confidence interval (CI); 0.56 to 0.94) and 0.89 (95 %CI; 0.70 to 0.97) for specificity. Conclusions The diagnostic evidence of available health apps on Apple's and Google's app stores is scarce. Consumers and healthcare professionals should be aware of this when using or recommending them.
Data for PONE-D-17-20084 Smartphone Study
<p>1. Full ERP data processed, segmented , averaged</p> <p>2. Full behavioral data</p>
Supplementary material 1 from: Thanayutsiri T, Charoenying T, Patrojanasophon P, Pamornpathomkul B, Opanasopit P, Ngawhirunpat T, Rojanarata T (2023) Facile, sensitive and reagent-saving smartphone-based digital image colorimetric assay of captopril tablets enabled by long-pathlength RGB acquisition. Pharmacia 70(4): 1511-1519. https://doi.org/10.3897/pharmacia.70.e114927
Supplementary data
Time variation of accelerometer sensor data from a smartphone placed on the same surface next to the mobilefuge
<p>Time variation of accelerometer sensor data from a smartphone placed on the same surface next to the mobilefuge is recorded to show the vibrations caused by the mobilefuge.</p> <p>This data set has three csv files that are used to create the Figure 9 in the mobilefuge article. </p> <p>Figure.9a_mobilefuge_off.csv</p> <p>Fugure.9b_mobilefuge_on.csv</p> <p>Figure.9c_mobilefuge_with_pad.csv</p> <p>The labels in the first row of each of the file are Time (s), acceleration along the x-direction (m/s^2), acceleration along the y-direction (m/s^2) and acceleration along the z-direction (m/s^2).</p>
Healing the battery and the planet: an environmental perspective on self-healing batteries for smartphones
<p>The data contains the databases used to calculate the environmental impacts of a self-healing battery including full Life Cycle Inventory data published in the article entitled "Healing the battery and the planet: an environmental perspective on self-healing batteries for smartphones".</p>
Smartphone Addiction and Its Role in Cultivating Customer Loyalty Among Women - Dataset
<div> <div> <div> <p>Smartphone Addiction and Its Role in Cultivating Customer Loyalty Among Women - Dataset</p> </div> </div> </div>
A Potential Method for Identifying Milk Adulteration and Pb(II) Contamination Scenarios Using Principal Component Analysis from Smartphone Photographs
<p>Early Research Data</p>
Recordings of classical music (voice with piano, piano solo) with smartphones and professional audio equipment
<p>To investigate differences of performance rating and perception of classical music demo videos, two demos were recorded with six devices (four Smartphones with main cam video function, one field recorder, one professional setup). Video and Audio were separated for each file, only the audio files were used in the study and are thus presented here. The music of the voice demo is from the genres of romantic lied and romantic and modern opera, the piano solo music was composed in the 20th century.</p> <p>The documentation follows the recommendations of the German Society for Acoustics (DEGA), the information is as following:</p> <p>A 3D model of the recording situation.<br>The audio files, normalised (as used in the corresponding study) and with original level.<br>Geometric measurements of room dimensions.<br>Pictures of the recording.<br>A list of the equipment and recording system.<br>Render statistics (provided by the DAW used, Reaper).<br>Scores of two of the three pieces.<br>A Takelist.</p>
Supplementary Materials article : Risk Estimation of Severe Primary Graft Dysfunction in Heart Transplant Recipients Using a Smartphone
Open the record for dataset details and reuse information.
Data from: Evidence to support common application switching behaviour on smartphones
We find evidence to support common behaviour in smartphone usage based on analysis of application (app) switching. This is an overlooked aspect of smartphone usage that gives additional insight beyond screen time and the particular apps that are accessed. Using a dataset of usage behaviour from 53 participants over a 6-week period, we find strong similarity in the structure of networks built from app switching, despite diversity in the apps used, and the volume of app switching. App switch networks exhibit small-world, broad-scale network features, with a rapid popularity decay, suggesting that preferential attachment may drive next-app decision making.
Smartphone-Based Incentive Framework for Dynamic Network-Level Traffic Congestion Management Project H3
<p>Task 2 numerical experiment results</p>
Datasets and Supporting Materials for the IPIN 2022 Competition Track 3 (Smartphone-based, off-site)
<p>This package contains the datasets and supplementary materials used in the IPIN 2022 Competition.</p> <p><strong>Contents:</strong></p> <ul> <li>Track-3_TA-2022.pdf: Technical annex describing the competition (Version 2)</li> <li>01 Logfiles: This folder contains a subfolder with the 89 training trials a subfolder with the 24 testing trials (validation), and a subfolder with the 3 blind scoring trials (test) as provided to competitors.</li> <li>02 Supplementary_Materials: This folder contains the matlab/octave parser, the raster maps, the files for the matlab tools and the trajectory visualization.</li> <li>03 Evaluation: This folder contains the scripts used to calculate the competition metric, the 75th percentile on the 31|61|61 evaluation points. It requires the Matlab Mapping Toolbox. The ground truth is also provided as 3 csv files. Since the results must be provided with a 2Hz freq. starting from apptimestamp 0, the GT files include the closest timestamp matching the timing provided by competitors for the 3 evaluation logfiles. It contains samples of reported estimations and the corresponding results.</li> </ul> <p><strong>Please, cite the following works when using the datasets included in this package:</strong></p> <ul> <li>Torres-Sospedra, J.; et al. Datasets and Supporting Materials for the IPIN 2022 Competition Track 3 (Smartphone-based, off-site), Zenodo 2022. http://dx.doi.org/10.5281/zenodo.7612915</li> </ul>
Feasibility and Acceptability of a Smartphone App to Assess Early Warning Signs of Psychosis Relapse
ClinicalTrials.gov study NCT03558529. IPD Sharing: UNDECIDED. Countries: 0. Publications: 17.
PainSquad+: A Smartphone App to Support Real-time Pain Management for Adolescents With Cancer
ClinicalTrials.gov study NCT02901834. IPD Sharing: Not stated. Countries: 0. Publications: 2.
Cervical Parameters and Body Awareness in Relation to Smartphone Addiction
ClinicalTrials.gov study NCT06598774. IPD Sharing: UNDECIDED. Countries: 1. Publications: 7.
A Smartphone-Based Intervention to Improve Colorectal Cancer Screening in African American Men
ClinicalTrials.gov study NCT06052202. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Impact of a Smartphone App on the Quality of Pediatric Colonoscopy Preparations
ClinicalTrials.gov study NCT04590105. IPD Sharing: YES. Countries: 0. Publications: 15.
Breakthrough Anxiety and Sleep Evaluation Using Linked Devices and Smartphone Application Onar (BASEL)
ClinicalTrials.gov study NCT06027047. IPD Sharing: NO. Countries: 0. Publications: 4.
Smartphone-Based Exposure Treatment for Dental Anxiety
ClinicalTrials.gov study NCT03461016. IPD Sharing: NO. Countries: 1. Publications: 0.
An Innovative Smartphone Application for Adverse Event Management During Breast Cancer Adjuvant Chemotherapy
ClinicalTrials.gov study NCT05258461. IPD Sharing: NO. Countries: 0. Publications: 2.
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.