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.

842

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

842 results for “Smartphone”

Learn how ShareScore rates datasets ↗
ClinicalTrials.gov36/100

Evaluating Household Food Behavior With a Smartphone App

ClinicalTrials.gov study NCT03309306. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov36/100

Smartphone-based Utility of the Vestibulo-ocular Reflex

ClinicalTrials.gov study NCT06856746. IPD Sharing: YES. Countries: 1. Publications: 8.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov36/100

A Smartphone-based Application Post-myocardial Infarction to Manage Cardiovascular Disease Risk

ClinicalTrials.gov study NCT03416920. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov36/100

Step Away: Comparing a Chatbot-delivered Alcohol Intervention With a Smartphone App

ClinicalTrials.gov study NCT04447794. IPD Sharing: Not stated. Countries: 1. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov36/100

The Influence of a Medication Adherence Smartphone Application on Medication Adherence in Chronic Illness

ClinicalTrials.gov study NCT05098743. IPD Sharing: NO. Countries: 1. Publications: 2.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov36/100

A Smartphone Intervention for WIC Mothers to Improve Nutrition and Weight Gain During Pregnancy

ClinicalTrials.gov study NCT04028843. IPD Sharing: NO. Countries: 1. Publications: 4.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov36/100

Impact of Preanesthetic Information and Behavioral Intervention Using Smartphone on Anxiety of Children

ClinicalTrials.gov study NCT02246062. IPD Sharing: Not stated. Countries: 1. Publications: 23.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov36/100

Evaluation of a New 6 Minute Walk Test Smartphone App in Patients With Pulmonary Hypertension

ClinicalTrials.gov study NCT04633538. IPD Sharing: UNDECIDED. Countries: 1. Publications: 8.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov36/100

Smartphone and 3D Printing Based Home Rehabilitation System for Chronic Stroke

ClinicalTrials.gov study NCT04363944. IPD Sharing: YES. Countries: 1. Publications: 2.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov36/100

CareConekta: A Smartphone App to Improve Engagement in HIV Care

ClinicalTrials.gov study NCT03836625. IPD Sharing: YES. Countries: 1. Publications: 4.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov36/100

Can a Smartphone App That Includes a Chatbot-based Coaching and Incentives Increase Physical Activity in Healthy Adults?

ClinicalTrials.gov study NCT03384550. IPD Sharing: YES. Countries: 1. Publications: 2.

controlledIPD-YESFeb 2026View details →
dryad36/100

Data from: Advancing mold identification in the routine laboratory: Performance of smartphone-based imaging and a newly developed Convolutional Neural Network

Open the record for dataset details and reuse information.

publicNov 2025View details →
dryad36/100

Emergent smartphone users' dataset

Open the record for dataset details and reuse information.

publicNov 2021View details →
dryad36/100

Risky decision and happiness task: The Great Brain Experiment smartphone app

Open the record for dataset details and reuse information.

publicMar 2023View details →
dryad36/100

Effect of smartphone location on pharmacy students’ attention and working memory

Open the record for dataset details and reuse information.

publicFeb 2024View details →
dryad36/100

Source Data for Crowdsourcing Bridge Dynamic Monitoring with Smartphone Vehicle Trips

Open the record for dataset details and reuse information.

publicNov 2022View details →
zenodo32/100

Supplementary evaluation files for the paper: Grid-Based Bayesian Filtering Methods for Pedestrian Dead Reckoning Indoor Positioning Using Smartphones

<p>This package contains evaluation supplementary files for the paper:&nbsp;<em>Grid-Based Bayesian Filtering Methods for Pedestrian Dead Reckoning Indoor Positioning Using Smartphones</em> by Miroslav Opiela and Franti&scaron;ek Galč&iacute;k.</p> <p><strong>Contents:&nbsp;</strong></p> <ul> <li>ground_truth - real positions of checkpoints for given input files</li> <li>input - sensor measurements recordings with initial positions (also after floor transitions) and checkpoint&nbsp;labels&nbsp;</li> <li>maps - processed map models containing positions of points and connections (e.g., walls) in custom coordinate system. Reference to GNSS and map rotation is inducted in maps-meta.xml</li> <li>output - data&nbsp;processed by the localization system. JSON containing the applied method,&nbsp;its configuration, and&nbsp;all estimated positions. Errors for every folder are summarized in the csv file</li> <li>visualization - trajectories visualized for selected output files</li> <li>readme.txt - describes data formats used for particular files in this dataset and summarizes output files</li> </ul> <p><strong>Venues</strong></p> <p>Data are recorded in three buildings:</p> <ul> <li>codename: SA1, SA1_rotated&nbsp;- recorded by the author in the&nbsp;faculty building (Park Angelinum 9, 04001, Ko&scaron;ice, Slovakia) using&nbsp;Lenovo tablet</li> <li>codename: AtlantisR0, AtlantisR-1, AtlantisR+1, AtlantisR+2 - the shopping mall Atlantis Le Centre (Boulevard Salvador Allende, 44800 Saint-Herblain, France). Dataset is from IPIN 2018 competition and&nbsp;loc_20180922_160206 is recorded by the author using Xiaomi Mi 5.</li> <li>codename: CNR_0, CNR_1, CNR_2 - the research institute building CNR (Via Giuseppe Moruzzi, 56127 Pisa, Italy). Dataset is from IPIN 2019 competition.&nbsp;</li> </ul> <p><strong>Used datasets</strong></p> <p>A subset of input data is derivated from available logfiles provided by organizers of&nbsp;IPIN 2018 and IPIN 2019 competitions:</p> <ul> <li>Jimenez, A.R.; Mendoza-Silva, G.M.; Ortiz, M.; Perez-Navarro, A.; Perul, J.;&nbsp;Seco, F.; Torres-Sospedra, J.&nbsp;Datasets and Supporting Materials for the IPIN 2018 Competition Track 3 (Smartphone-based, off-site).&nbsp;<a href="http://dx.doi.org/10.5281/zenodo.2823964">http://dx.doi.org/10.5281/zenodo.2823964</a></li> <li>Jim&eacute;nez, A. R.; Perez-Navarro, A.; Crivello, A.; Mendoza-Silva, G.; Ortiz, M.; Perul, J.; &nbsp;Seco, F. and Torres-Sospedra, J. Datasets and Supporting Materials&nbsp;for the IPIN 2019 Competition Track 3 (Smartphone-based, off-site), Zenodo 2019.&nbsp;<a href="http://dx.doi.org/10.5281/zenodo.3606765">http://dx.doi.org/10.5281/zenodo.3606765</a>&nbsp;&nbsp; &nbsp;</li> </ul> <p><strong>Funding</strong></p> <p>The work was partially supported by the Slovak Grant Agency of the Ministry of Education and Academy of Science of the Slovak Republic under grant no. 1/0056/18 and by the Slovak Research and Development Agency under the contract no. APVV-15-0091.</p> <p><strong>Contact</strong></p> <p>For any further questions, please contact:</p> <p>Miroslav Opiela, miroslav.opiela@upjs.sk&nbsp;Institute of Computer Science, Faculty of Science, P. J. &Scaron;af&aacute;rik University (UPJS), Ko&scaron;ice, Slovakia</p>

opencc-by-4.0Aug 2020View details →
zenodo32/100

Período de um pêndulo utilizando o sensor de luminosidade de um Smartphone e o aplicativo Phyphox

<p>Neste Tutorial&nbsp;&nbsp;vamos utilizar o aplicativo de celular phyphox como instrumento para coleta de dados acerca do per&iacute;odo de um p&ecirc;ndulo. Os valores obtidos conduzem ao valor da acelera&ccedil;&atilde;o da gravidade local com bom grau de aproxima&ccedil;&atilde;o e erro estat&iacute;stico ou precis&atilde;o na medida da ordem de 3% e Exatid&atilde;o da ordem de 1,1%. Outras medidas foram realizadas conduzindo a valores sempre desta ordem de grandeza.</p> <p>Propostas de experimenta&ccedil;&atilde;o para aulas remotas. Espero que apreciem esta proposta e que possa contrinuir com suas aulas presenciais ou remotas</p>

opencc-by-4.0Nov 2020View details →
zenodo32/100

Are Smartphones and Fitness Apps Fit For Purpose? An experimental study.

<p>Data set for treadmill and fitness apps study</p>

opencc-zeroFeb 2016View details →
zenodo32/100

Smartphones

<p>Dataset de smartphones</p> <p>jplazaf@uoc.edu</p> <p>dvilloria@uoc.edu</p>

opencc-by-4.0Apr 2024View 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