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.
592
datasets available to search
ShareScore release 0.9.0
Dataset results
592 results for “Cross-Sectional Studies”
MiRoR7-P1- Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design
<p>dataset referring to </p> <p><strong>Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design</strong></p> <p> </p> <p> </p> <p>Lorenzo Bertizzolo<sup>1</sup>, Patrick M Bossuyt<sup>2</sup>, Ignacio Atal<sup>1, 5</sup>, Philippe Ravaud<sup>1, 3-6</sup>, Agnès Dechartres<sup>7</sup></p> <p> </p> <p><sup>1</sup> INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of therapeutic evaluation of chronic diseases Team (METHODS), Paris, F-75004 France; Paris Descartes University, Sorbonne Paris Cité, France.</p> <p><sup>2</sup> Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Netherlands.</p> <p><sup>3</sup> Centre d’Épidémiologie Clinique, Hôpital Hôtel Dieu, AP-HP (Assistance Publique des Hôpitaux de Paris), Paris, France.</p> <p><sup>4</sup> Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.</p> <p><sup>5</sup> Cochrane France, Paris, France</p> <p><sup>6</sup> Columbia University, Mailman School of Public Health, Department of Epidemiology, New York, USA</p> <p><sup>7</sup> Sorbonne Université, INSERM, Institut Pierre Louis de Santé Publique, Département Biostatistique, Santé Publique et Information Médicale, AP-HP, Hôpitaux Universitaires Pitié Salpêtrière – Charles Foix, Paris, France</p>
Socioeconomic status and adiposity in childhood cancer survivors: A cross-sectional retrospective study
<p>This dataset contains information on selected indicators of socioeconomic status and anthropometric indicators of adiposity in a population of childhood cancer survivors from the Late Effect Outpatient Clinic at St. Anne's Hospital in Brno, Czech Republic. </p>
General practice characteristics associated with life expectancy of practice populations: a cross-sectional study
<p>The dataset was used to investgate features of general practice associated with life expectancy of general practice populations in England for the period 2015-2019.</p>
Data from a cross-sectional study of fifth grade children in a sample of primary schools in Belgium that differ in amount of greenness at school and landscape level
<p>The data in this deposit were collected as part of the <code>B@SEBALL</code> project (Biodiversity at School Environments - Benefits for All). </p> <p>The project investigated how biodiversity in the school environment can positively affect children’s health and mental well-being. <code>B@SEBALL</code> also investigated the opportunities for reducing health inequalities among children via biodiversity at school environments.</p> <p>The data are organized according to the <a href="https://specs.frictionlessdata.io/data-package/">Frictionless Data Package standard</a>. All child-level and school-level data have been anonymized. Each data package is a collection of <code>csv</code> files and a <code>json</code> file. The <code>json</code> file holds descriptive information for all variables in all <code>csv</code> files. The <code>zip</code> file contains two frictionless data packages. The data packages contain information on 37 primary schools and 513 children. </p> <p>The data package, <code>data_package_an_zenodo_cleaned_data</code>, contains the original data in a tidied and cleaned format. It consists of 46 <code>csv</code> files. The files relate to the following contents:</p> <table> <tbody> <tr> <td><strong>contents</strong></td> <td><strong>filename</strong></td> </tr> <tr> <td>metadata file</td> <td>datapackage.json</td> </tr> <tr> <td>landscape level variables</td> <td>wp1_landscape_level_data.csv</td> </tr> <tr> <td>metadata about participants</td> <td>wp2_participants_metadata.csv</td> </tr> <tr> <td>general school level data</td> <td>wp2_school_data.csv</td> </tr> <tr> <td>pollution data at school level</td> <td>wp3_ua_sirm_data.csv</td> </tr> <tr> <td>classroom data about air quality</td> <td>wp3_ucl_classroom_airquality.csv</td> </tr> <tr> <td>area of ecotopes in the school environment</td> <td>wp3_ucl_ecotope_categories.csv</td> </tr> <tr> <td>greenness indicators for the school environment derived from ecotopes</td> <td>wp3_ucl_greenness_indicators.csv</td> </tr> <tr> <td>greenness indicators for the school environment derived from ecotopes</td> <td>wp3_ucl_greenness_key.csv</td> </tr> <tr> <td>greenness indicators for the school environment derived from ecotopes</td> <td>wp3_ucl_greenpatches.csv</td> </tr> <tr> <td>playground biodiversity indicators</td> <td>wp3_ucl_playground_biodiversity.csv</td> </tr> <tr> <td>d2-test of attention data</td> <td>wp4_d2_data_by_child.csv</td> </tr> <tr> <td>d2-test of attention data</td> <td>wp4_d2_data_by_line.csv</td> </tr> <tr> <td>d2-test of attention data</td> <td>wp4_d2_data_by_linegroup.csv</td> </tr> <tr> <td>Self-reported allergy data</td> <td>wp4_isaac_data.csv</td> </tr> <tr> <td>Self-reported allergy data</td> <td>wp4_isaac_questions.csv</td> </tr> <tr> <td>Self-reported well-being data</td> <td>wp4_kidscreen_data.csv</td> </tr> <tr> <td>Self-reported well-being data</td> <td>wp4_kidscreen_questions.csv</td> </tr> <tr> <td>Self-reported attitude toward outdoor play</td> <td>wp5_atop_data.csv</td> </tr> <tr> <td>Self-reported attitude toward outdoor play</td> <td>wp5_atop_questions.csv</td> </tr> <tr> <td>Guardian-reported general questions</td> <td>wp5_guardians_general_questions_data.csv</td> </tr> <tr> <td>Guardian-reported general questions</td> <td>wp5_guardians_general_questions_key.csv</td> </tr> <tr> <td>Guardian-reported protection from risk</td> <td>wp5_guardians_risk_protection_data_part1.csv</td> </tr> <tr> <td>Guardian-reported protection from risk</td> <td>wp5_guardians_risk_protection_data_part2.csv</td> </tr> <tr> <td>Guardian-reported protection from risk</td> <td>wp5_guardians_risk_protection_key.csv</td> </tr> <tr> <td>Self-reported nature connectedness</td> <td>wp5_nc_data.csv</td> </tr> <tr> <td>Self-reported nature connectedness</td> <td>wp5_nc_key.csv</td> </tr> <tr> <td>Parent-reported allergy data</td> <td>wp5_parents_allergy_related_questions_data.csv</td> </tr> <tr> <td>Parent-reported allergy data</td> <td>wp5_parents_allergy_related_questions_key.csv</td> </tr> <tr> <td>Parent-reported cultural background</td> <td>wp5_parents_cultural_background_data.csv</td> </tr> <tr> <td>Parent-reported cultural background</td> <td>wp5_parents_cultural_background_key.csv</td> </tr> <tr> <td>Parent-reported general questions</td> <td>wp5_parents_general_questions_data.csv</td> </tr> <tr> <td>Parent-reported general questions</td> <td>wp5_parents_general_questions_key.csv</td> </tr> <tr> <td>Parent-reported independent mobility data</td> <td>wp5_parents_independent_mobility_data.csv</td> </tr> <tr> <td>Parent-reported independent mobility data</td> <td>wp5_parents_independent_mobility_key.csv</td> </tr> <tr> <td>Parent-reported living environment</td> <td>wp5_parents_living_environment_data.csv</td> </tr> <tr> <td>Parent-reported living environment</td> <td>wp5_parents_living_environment_key.csv</td> </tr> <tr> <td>Parent-reported outdoor play characteristics</td> <td>wp5_parents_outdoor_play_data_part1.csv</td> </tr> <tr> <td>Parent-reported outdoor play characteristics</td> <td>wp5_parents_outdoor_play_data_part2.csv</td> </tr> <tr> <td>Parent-reported outdoor play characteristics</td> <td>wp5_parents_outdoor_play_data_part3.csv</td> </tr> <tr> <td>Parent-reported outdoor play characteristics</td> <td>wp5_parents_outdoor_play_data_part4.csv</td> </tr> <tr> <td>Parent-reported outdoor play characteristics</td> <td>wp5_parents_outdoor_play_key.csv</td> </tr> <tr> <td>Parent-reported risk protection data</td> <td>wp5_parents_risk_protection_data_part1.csv</td> </tr> <tr> <td>Parent-reported risk protection data</td> <td>wp5_parents_risk_protection_data_part2.csv</td> </tr> <tr> <td>Parent-reported risk protection data</td> <td>wp5_parents_risk_protection_key.csv</td> </tr> <tr> <td>Parent-reported data relating to socio-economic status</td> <td>wp5_parents_ses_questions_data.csv</td> </tr> <tr> <td>Parent-reported data relating to socio-economic status</td> <td>wp5_parents_ses_questions_key.csv</td> </tr> </tbody> </table> <p> </p> <p>The <code>data_package_an_zenodo_derived_data</code> data package, contains derived data that was calculated based on input from <code>data_package_an_zenodo_cleaned_data</code> at either child-level or at school-level.</p> <table> <tbody> <tr> <td><strong>contents</strong></td> <td><strong>filename</strong></td> </tr> <tr> <td>metadata file</td> <td>datapackage.json</td> </tr> <tr> <td>derived data at child level</td> <td>wp1_child_level_key_variables.csv</td> </tr> <tr> <td>derived attention score based on d2-test data, aggregated to line-level</td> <td>wp1_d2_by_line_attention_score.csv</td> </tr> <tr> <td>derived data at school level</td> <td>wp1_school_level_key_variables.csv</td> </tr> </tbody> </table> <p>These data packages only store information for participants that gave consent for a particular part of the study and that gave consent for long-term storage of the data. There may therefore be slight differences between results published as part of the project consortium, which could make use of participant data that did not give consent for long-term data storage, and reproduction of these results based on the data in this data repository. We also note that the derived variables in the derived data package were calculated with these participants included and removal of participants for which we had no long-term storage consent was done after these calculations.</p> <p>As part of the project, microbiome data were also collected (both from cheek swabs on the children and from environmental samples), but this part of the data are not a part of this deposit and will be deposited in the European Nucleotide Archive (ENA).</p>
Prevalence of Multimorbidity among Urban–Rural Older Adults in Mongolia: A Cross-Sectional Study
<p>A face-to-face, questionnaire-based cross-sectional study was conducted with 800 valid participants aged ≥60 years in Mongolia from June to September 2023.</p>
Diagnostic strategies for muscular dystrophies: a Cross-Sectional Study
<p>Datos obtenido producto de un estudio de corte transversal con el fin de establecer la prevalencia de base hospitalaria en distrofias musculares, a través de un diseño de muestreo en fases.</p>
The Psychological Burden of the COVID-19 Pandemic and Its Associated Factors among the Frontline Doctors of Bangladesh: A Cross-sectional Study-Extended Data
<p>Using this document, we tried to assess the mental health status of the frontline doctors of Bangladesh during Coronavirus 2019 pandemic.</p>
Predictors of medical staff's knowledge, attitudes, and behavior of dysphagia assessment: A cross-sectional study
<p>This study aimed to develop training resources and standardize the assessment of dysphagia in patients with stroke. This study was a cross-sectional study. A total of 430 nurses and doctors from four provinces(Guangdong Province, Hunan Province, Guangxi Province, and Shaanxi Province) who were selected by convenience sampling were invited to complete the questionnaire through WeChat, DingTalk, and Tencent QQ from May 23 to 31, 2022. A self-reported questionnaire was used to assess participants' Knowledge, Attitude, and Behavior regarding dysphagia. Participants' sociodemographic, training, and nursing experience were measured using the general information sheet and assessed as potential predictors of medical staff's Knowledge, Attitudes, and Behavior of dysphagia assessment. A multiple linear regression model was used to identify the factors predicting medical staff's Knowledge, Attitudes, and Behavior regarding dysphagia assessment. The mean scores for Knowledge, Attitudes, and Behavior of dysphagia assessments were 92.654(SD 17.519). Multiple linear regression results indicated that experience in dysphagia patients' nursing, related training for dysphagia, working years in the field of dysphagia-related diseases, specialized training in geriatric, swallowing & rehabilitation, and department related to neurology, rehabilitation & elderly were significant predictors, accounting for 35.1% of the variance in scores of medical staff's Knowledge, Attitudes and Behavior of dysphagia assessment. Our findings imply that nursing experience, training, and work for patients with swallowing disorders could have positive effects on the Knowledge, Attitudes, and Behavior of medical staff regarding dysphagia assessment. Hospital administrators should provide relevant resources, such as videos of dysphagia assessment, training centers for the assessment of dysphagia, and swallowing specialist nurses. It is important that health policies fully recognize the role of training and support systems in caring for people with dysphagia.</p>
Data for "Impact of early cleft lip and palate surgery on maxillary growth in 5- and 10-Year-old patients with unilateral cleft lip and palate: a cross-sectional study"
<p>Relative frequency in % (absolute frequency is shown above each bar). Frequency of 5YO indices in cleft patients and frequency of GOSLON indices in cleft patients.</p>
Dataset of the study "Thirty seconds sit-to-stand test as an alternative for estimating peak oxygen uptake and six-minutes walking distance in women with breast cancer: a cross-sectional study"
<p>Data was collected to study the usefulness of the thirty seconds sit-to-stand test as an alternative for estimating peak oxygen uptake and six-minutes walking distance in women with breast cancer, which is a cross-sectional study derived from the ONCORE project (Randomized controlled trial on comprehensive exercise-based cardiac rehabilitation program for the prevention of anthracyclines and/or anti-HER2 antibodies-induced cardiotoxicity in breast cancer), ClinicalTrials.gov Identifier: NCT03964142</p> <p> </p> <p>DATASET FILE (xlsx) includes 4 sheets:<br> - Dataset_variables: all variables collected pre-post intervention<br> - Descriptive data (baseline): variables used for the descriptive analysis before the intervention (baseline)<br> - Data_CPET-30STS(pre-post): pooled data from CPET-30STS pre-post intervention<br> - Data_6MWD-30STS(pre-post): pooled data from 6MWD-30STS pre-post intervention</p>
Data for "Associations between 3D surface scanner derived anthropometric measurements and body composition in a cross-sectional study"
<p>Datasets underlying the analysis of the paper: "Associations between 3D surface scanner derived anthropometric measurements and body composition in a cross-sectional study"</p> <p>This upload includes the following:</p> <ul> <li><strong>data_study.csv </strong>: contains socio-demographic, health- and lifestyle factors, and body scan variables of each participant</li> <li><strong>healthscore.csv</strong> : contains the "healthy score" from the food frequency questions calculated from from five food categories: fruits, vegetables, wholegrain products, meat, and sweet/salty snacks. For each category the officially recommended minimum or maximum amount of weekly intake was used as the cut-off value and a point was assigned if the recommendation was met. A score from 0 to 5 was built to reflect the overall healthiness of the diet.</li> </ul>
Evaluating the Prevalence and Impact of Chronic Ankle Insta-bility in Collegiate Athletes across Various Sports: A Cross-Sectional Study.
<p>In the cross-sectional study "Evaluating the Prevalence and Impact of Chronic Ankle Instability in Collegiate Athletes across Various Sports," researchers sought to quantify how widespread chronic ankle instability (CAI) is among collegiate athletes and to determine its effects on athletic performance and training. The study involved 385 athletes from diverse sports, including basketball, soccer, track and field, swimming, and other sports, and revealed that CAI was present in nearly half of the participants. The investigation highlighted significant disparities in prevalence rates among different sports, with basketball and soccer athletes exhibiting higher rates of CAI. Furthermore, the study assessed the impact of CAI on several performance metrics such as training intensity, performance scores, and recovery times, finding that athletes with CAI generally showed lower performance levels and longer recovery times. These results emphasize the need for targeted preventive and rehabilitative strategies to mitigate the effects of CAI and support athlete health and performance.</p>
Dataset of the publication "Cross-sectional study of prevalence of dementia, behavioural symptoms, mobility, pain and other health parameters in nursing homes in Austria and the Czech Republic: results from the DEMDATA project"
<p>Dataset of the publication Stefanie R. Auer , Margit Höfler, Elisabeth Linsmayer, Anna Beránková, Doris Prieschl, Paulina Ratajczak,<br> Michal Šteffl and Iva Holmerová (2018) "Cross-sectional study of prevalence of dementia, behavioural symptoms, mobility, pain and other health parameters in nursing homes in Austria and the Czech Republic: results from the DEMDATA project"</p>
BioAge: A cross-sectional study into the relationship between childhood socieconomic status
<p>R script and data files for Masters of Research project into the effect of childhood SES on biological ageing in young adults.</p>
Data and R-code on a cross-sectional study of factors associated with lameness in dairy cows housed in freestall and compost-bedded pack dairy farms in southern Brazil
<p>The data correspond to a cross-sectional study designed to investigate factors associated with lameness in dairy cows on intensive farms in southern Brazil.<br> Farms: 38 freestall and 12 compost-bedded pack visited once in 2016. All lactating cows (n = 13,716) were examined and body condition score (BCS) and gait score were assessed. Additionally, some variables were collected through inspection of facilities and using data from an interview with farmers on routine herd management practices.<br> Additional information is provided in the published paper ("Factors associated with lameness prevalence in lactating cows housed in freestall and compost-bedded pack dairy farms in southern Brazil" https://doi.org/10.1016/j.prevetmed.2019.104773)</p>
Data from: Variations in regional white matter volumetry and microstructure during the post-adolescence period: a cross-sectional study of a cohort of 1,713 university students
<p>Human brain white matter undergoes a protracted maturation that continues well into adulthood. Recent advances in diffusion-weighted imaging (DWI) methods allow detailed characterisations of the microstructural architecture of white matter, and they are increasingly utilised to study white matter changes during development and ageing. However, relatively little is known about the late maturational changes in the microstructural architecture of white matter during post-adolescence. Here we report on regional changes in white matter volume and microstructure in young adults undergoing university-level education. As part of the MRi-Share multi-modal brain MRI database, multi-shell, high angular resolution DWI data were acquired in a unique sample of 1,713 university students aged 18 to 26. We assessed the age and sex dependence of diffusion metrics derived from diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) in the white matter regions as defined itein the John Hopkins University (JHU) white matter labels atlas. We demonstrate that while regional white matter volume is relatively stable over the age range of our sample, the white matter microstructural properties show clear age-related variations. Globally, it is characterised by a robust increase in neurite density index (NDI), and to a lesser extent, orientation dispersion index (ODI). These changes are accompanied by a decrease in diffusivity. In contrast, there is minimal age-related variation in fractional anisotropy. There are regional variations in these microstructural changes: some tracts, most notably cingulum bundles, show a strong age-related increase in NDI coupled with decreases in radial and mean diffusivity, while others, mainly cortico-spinal projection tracts, primarily show an ODI increase and axial diffusivity decrease. These age-related variations are not different between males and females, but males show higher NDI and ODI and lower diffusivity than females across many tracts. These findings emphasize the complexity of changes in white matter structure occurring in this critical period of late maturation in early adulthood.</p>
Seroprevalence of IgG antibodies against SARS coronavirus 2 in Belgium – a serial prospective cross-sectional nationwide study of residual samples (March – October 2020)
<p>This dataset contains information on seven prospective cross-sectional nationwide residual sera collection rounds. The samples were analyzed for IgG antibodies against S1 proteins of SARS-CoV-2 with a semi-quantitative commercial ELISA (EuroImmun, Luebeck, Germany).</p> <p>We provide a CSV file containing the following variables:</p> <ul> <li><strong>code</strong>: unique sample code</li> <li><strong>age_cat</strong>: age categories by 10-year age bands (0-10, 10-20, ..., 80-90, 90-Inf), the lower limit is included, e.g. 0-10 = [0,10)</li> <li><strong>sex</strong>: sex (f = female, m = male)</li> <li><strong>province</strong>: province of residence (11 categories)</li> <li><strong>region</strong>: region of residence (3 categories: Brussels, Flanders, Walloon)</li> <li><strong>collection_round</strong>: collection round (values 1 to 7)</li> <li><strong>collection_start</strong>: start date of the collection round</li> <li><strong>collection_end</strong>: end date of the collection round</li> <li><strong>igg_orig</strong>: measured IgG OD value as character (note, a semi-quantitative ELISA was used, i.e. this should not be interpreted continiously)</li> <li><strong>igg_cat</strong>: categorized IgG OD values <ul> <li><em>LoD</em>: IgG OD < 0.15</li> <li><em>negative</em>: 0.15 ≤ IgG OD < 0.8</li> <li><em>borderline</em>: 0.8 ≤ IgG OD < 1.1</li> <li><em>positive</em>: 1.1 ≤ IgG OD</li> </ul> </li> </ul> <p>Please see publication mentioned underneath for more details (<a href="https://doi.org/10.1101/2020.06.08.20125179">https://doi.org/10.1101/2020.06.08.20125179</a>).</p> <p><strong>Funding:</strong> This work received funding from the European Union's Horizon 2020 research and innovation program - project EpiPose (No 101003688), the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement 682540 TransMID), the Flemish Research Fund (FWO 1150017N) and from The Antwerp University Fund; which is a community of donors who contribute to research and education with their personal commitment through a donation, gift, bequest or through academic chairs. The funders had no role in study design, data collection, data analysis, data interpretation, writing or submitting of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.</p>
Dataset for the paper "The relationship between medical students' empathy, mental health, and burnout: A cross-sectional study" published in Medical Teacher (2022)
<p><strong>Full reference of the paper: </strong></p> <p>Valerie Carrard, Céline Bourquin, Sylvie Berney, Katja Schlegel, Jacques Gaume, Pierre-Alexandre Bart, Martin Preisig, Marianne Schmid Mast & Alexandre Berney (2022): The relationship between medical students’ empathy, mental health, and burnout: A cross-sectional study, Medical Teacher, DOI: <a href="https://doi.org/10.1080/0142159X.2022.2098708">10.1080/0142159X.2022.2098708</a></p>
Development Gateway shisha study quantitative data: a cross-sectional survey investigating factors associated with shisha use in Nigeria
<p>This data is from a cross-sectional telephone survey among 1278 respondents (611 current shisha smokers and 667 shisha non-smokers) exploring the following questions:</p> <ol> <li>What factors (demographic, social, cultural, behavioural, etc.) are associated with the use of shisha in Nigeria?</li> <li>What are the shisha use patterns and behaviours among those who use shisha in Nigeria?</li> </ol> <p>The study was conducted across the six geo-political zones in Nigeria (North-East, North-West, North-Central, South-East, South-South and South-West) in the following states: Lagos, Oyo, FCT, Plateau, Gombe, Adamawa, Kaduna, Kano, Rivers, Edo, Anambra and Ebonyi.</p> <p>The data was collected between 28th July and 11th September 2022.</p> <p>Also included is the codebook and the study questionnaire.</p>
Delving into the relationship between regular physical exercise and cardiac interoception in two cross-sectional studies.
<p>This repository contains raw data from two studies corresponding to the article "No evidence of a relationship between regular physical exercise and cardiac interoception" by Yoris et al. In Study I, 45 resting EEG files are included for the Active (N = 24) and Inactive (N = 21) groups, both for the eyes closed and eyes open conditions. For Study II, there are 60 resting EEG files (30 Active/30 Inactive). Data are in EEGLAB format .set/fdt. The project is publicly available for free use and can be accessed at <a href="https://osf.io/xrsgn/">https://osf.io/xrsgn/</a>.</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.