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118 results for “Panel Data”
Data associated with the following publication: Developing the Playground Play Value and Usability Audit Tool (PVUA): An Evaluation of Content Validity via an Expert Panel
<p>This data set contains the supporting data associated with the following publication:</p> <p>Morgenthaler, T., Loebach, J., Lynch, H., Pentland, D., Kottorp, A., & Schulze, C. (in press). Developing the Playground Play Value and Usability Audit Tool (PVUA): An Evaluation of Content Validity via an Expert Panel. Children, Youth and Environments. [DOI was not yet available when the data set was published]</p> <p>The data set includes the following files:</p> <ul> <li>read me file [contains all relevant information to understand and reuse this data set] </li> <li>13 additional files [for description, see read me file]</li> </ul> <p>For more information, please contact the lead researcher, Thomas Morgenthaler (tom.morgenthaler@gmail.com or 121101888@umail.ucc.ie)</p> <p> </p>
Data from: Complex population structure and haplotype patterns in Western Europe honey bee from sequencing a large panel of haploid drones
<p>This vcf file contains 7.023.689 SNPs and 870 honey bee samples, as described in the paper "Complex population structure and haplotype patterns in Western Europe honey bee from sequencing a large panel of haploid drones" by Wragg et al., available at https://doi.org/10.1101/2021.09.20.460798 as preprint.</p> <p>Eight hundred and seventy haploid drone samples from several honey bee subspecies hybrids were sequenced and aligned to the HAv3.1 reference genome. Sequence read alignment and genotyping quality filters were used to obtain a selection of 7.023.689 high-quality SNPs. The file Diversity_Study_629_Samples.txt corresponds to the 629 unique samples that were used for the diversity study described in the paper and can be used to recreate the restricted diversity dataset using bcftools or an equivalent software.</p> <p>Having sequenced haploid drones, heterozygous SNPs resulting from duplicated regions could be filtered out and the data is phased.</p>
CEPHIA Evaluation Panel data for Maxim and Sedia Limiting Antigen Avidity assays
<p>CEPHIA Evaluation Panel dataset containing final ODn values for each assay. The first file contains results on all standard panel samples, and the second contains results on blinded control samples tested in replicate.</p>
Data from the parametric analysis of masonry panels with limit analysis
<p>For each one of the simulations performed from the parametric analysis of masonry panels with limit analysis, this database contains a .txt, a .vtk and a .png file. In the .txt file the elapse time and the collapse multiplier of each simulation can be found. The .vtk file contains all the geometry and displacement values of every masonry panel. Finally, the .png file presents the collapse mechanism obtained. </p>
Control panel created from 30 Nanopore sequencing data from the Human Pangenome Reference Consortium
<p>This is control panel for <a href="https://github.com/friend1ws/nanomonsv">nanomonsv</a> software, which is expected to exclude many false positives as well as improve computational cost. This is made by aligning 30 Nanopore sequencing data from Human Pangenome Reference Consortium to the GRCh38 reference genome (obtained from <a href="https://console.cloud.google.com/storage/browser/genomics-public-data/resources/broad/hg38/v0;tab=objects">here</a>) with <a href="https://github.com/lh3/minimap2">minimap2</a> version 2.24. <strong>When you use these control panels and publish, do not forget to credit to <a href="https://humanpangenome.org/data-use-protocol/">HPRC</a>!</strong></p>
Data from: Development of Single Nucleotide Polymorphism (SNP) Panel for determination of environmental influence on genome for wild Columbia River redband trout (Oncorhynchus mykiss gairdnerii) in Southwest Idaho streams
<p>DNA were derived from fin tissue samples taken from individual trout captured from Little Jacks Creek, Big Jacks Creek , and Duncan Creek of the Owyhee mountains and Keithly Creek and Upper Mann Creek in the Hitt mountains of Western Idaho, United States. Fin tissues were collected from individual trout from each stream during monthly sampling events in June through October 2020. </p> <p><em>DNA Extraction:</em> Extraction of DNA from caudal fin tissues were performed using Quick-DNA Miniprep Plus purification kits (Zymo Research Inc.©). Small sections of fin tissue (≤ 25 mg) were collected from each sample. This was mixed with a digesting solution comprised of ultra-pure water, solid tissue buffer (Zymo Research Inc.©) and proteinase K. All tissues were digested in sealed microcentrifuge tubes for at minimum 3 h at 55°C in a water bath. We then aliquoted 100 µL of digestion supernatant and combined with 200 µL of genomic binding buffer (Zymo Research Inc.©). DNA was eluted in 50, 75, and 100 µL of elution buffer to determine which volume provided sufficient DNA concentration for genotyping. After it was determined all quantities produced suitable concentrations, going forward, 50 µL of elution buffer used.</p> <p><em>Genotyping:</em> Following extraction, genotyping-in-thousands sequencing took place at the Hagerman National Fish Hatchery’s genetics research facility with the assistance of the Columbia River Intertribal Fish Commission (CRTFC). Genotyping protocols were as described in Campbell et al. (2015) and summarized below. First, samples were prepared for amplification via PCR by combining DNA extracts with a Qiagen Plus multiplex master mix and a species-specific pooled primer mix. This step added the Illumina sequencing primer sites to amplicons. Following the creation of the PCR cocktail, thermocycling was conducted for amplification. Amplified samples were then diluted 20-fold. Diluted samples were transferred to new 96-well PCR plates where two genetic indexes and barcodes provides a unique set of tagging primers to each well and plate. Tagged plates then underwent a second PCR step. After the second PCR, all DNA were transferred to Charm Biotech normalization plates where DNA was bound to wells, washed, and finally eluted. After normalization, all DNA was pooled together and a purification step using magnetized beads in two steps to selectively remove fragments of DNA that are both too large and too small for sequencing. Following purification, each plate was quantified via qPCR using Life Technologies QuantStudio 6 Flex Instrument (Life Technologies). Finally, sequencing was performed using an Illumina HiSeq 1500 instrument.</p> <p><strong>Ancillary peer-reviewed manuscripts:</strong><br> <em>Genotyping protocols</em><br> Campbell NR, Harmon SA, Narum SR. 2015. Genotyping-in-Thousands by sequencing (GT-seq): A cost effective SNP genotyping method based on custom amplicon sequencing. Mol Ecol Resour, 15: 855-867. https://doi.org/10.1111/1755-0998.12357<br> <em>SNP loci reference</em><br> Collins EE, Hargrove JS, Delomas TA, Narum SR. 2020. Distribution of genetic variation underlying adult migration timing in steelhead of the Columbia River basin. Ecology and Evolution, 10(17): 9486-9502. https://doi.org/10.1002/ece3.6641 </p> <p><strong>Data Use</strong>:<br> <em>License</em>: <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> <br> <em>Recommended Citation</em>: Wooding AP, Narum SR, Pradhan DS. 2022. Data from: Development of Single Nucleotide Polymorphism (SNP) Panel for determination of environmental influence on genome for wild Columbia River redband trout (Oncorhynchus mykiss gairdnerii) in Southwest Idaho streams (0.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7055582</p> <p>Funding for this project is provided by US National Science Foundation and Idaho EPSCoR through award: OIA-1757324 </p>
A Panel Data Set of Cryptocurrency Development Activity on GitHub
<p>Contents:</p> <ul> <li><strong>all-sorted-recovered-normalized-2018-01-21-to-2019-02-04.csv</strong>: CSV format of all data, sorted by date. This file contains some imputed values for missing data, and all fields across all repositories and normalized to "null". This is the most convenient form to use.</li> <li><strong>all-sorted-2018-01-21-to-2019-02-04.csv</strong>: CSV format of all, sorted by date. It is the raw data after processing the raw format.</li> <li><strong>raw-data-2018-01-21-to-2019-02-04.tar.gz</strong>: The raw format of data collected (S-expressions). Contains additional contributor data and CoinMarketCap data not currently in the CSV datasets.</li> <li><strong>recovered.patch</strong>: The modification on <strong>all-sorted-2018-01-21-to-2019-02-04.csv</strong> after recovering (imputing) data<strong>, </strong>showing what was recovered.</li> <li><strong>recovered-normalized.patch</strong>: The modification of <strong>all-sorted-2018-01-21-to-2019-02-04.csv </strong>after normalizing the recovered data set. Thus, patching <strong>all-sorted-2018-01-21-to-2019-02-04.csv </strong>with<strong> recovered.patch</strong>, then <strong>recovered-normalized.patch </strong>gives <strong>all-sorted-recovered-normalized-2018-01-21-to-2019-02-04.csv</strong></li> <li><strong>missing-dates.txt</strong>: Days for which we missed GitHub data collection (partial or completely).</li> </ul> <p>Related publications:</p> <pre><code>@inproceedings{van-tonder-crypto-oss-2019, title = {{A Panel Data Set of Cryptocurrency Development Activity on GitHub}}, booktitle = "International Conference on Mining Software Repositories", author = "{van~Tonder}, Rijnard and Trockman, Asher and {Le~Goues}, Claire", series = {MSR '19}, year = 2019 } @inproceedings{trockman-striking-gold-2019, title = {{Striking Gold in Software Repositories? An Econometric Study of Cryptocurrencies on GitHub}}, booktitle = "International Conference on Mining Software Repositories", author = "Trockman, Asher and {van~Tonder}, Rijnard and Vasilescu, Bogdan", series = {MSR '19}, year = 2019 }</code></pre> <p>Related code: <a href="https://github.com/rvantonder/CryptOSS">https://github.com/rvantonder/CryptOSS</a></p>
Panel data used in the paper ""The shadow price of irrigation water in major groundwater depleting countries"
<p>The panel data are used in an econometric analysis estimating Cobb-Douglas production functions that are subsequently used to calculate the shadow price (current marginal value) or irrigation water in 11 major groundwater depleting countries.</p>
The macroeconomic determinants of trade openness in Latin American countries: A panel data analysis
<p><strong><span>Background:</span></strong><span> Trade openness shows a positive impact on economic growth, supported by economic theory, and export diversification and economic complexity show a positive dynamic in trade openness in the world; however, a specificity is generated in South American countries. Therefore, the objective of the research is to analyse the macroeconomic determinants of trade openness in Latin American countries.</span></p> <p><strong><span>Methods: </span></strong><span>The research approach was quantitative and explanatory using panel data methodology from the databases of the World Bank, Harvard University and the Economic Commission for Latin America and the Caribbean for the period 2000-2020.</span></p> <p><strong><span>Results: </span></strong><span>The fixed effects panel data model showed that the variables that had a negative impact on trade openness were GDP, the economic complexity index and the logistic performance index, while the variables that had a positive impact were exports of high-tech products (a proxy for innovation), exports, imports, research and development expenditure and interregional trade in goods.</span></p> <p><strong><span>Conclusions: </span></strong><span>Therefore, during the analysis period of 2000-2020 in South America, based on the panel data analysis under fixed effects, a total of 8 countries had a negative impact on trade openness, and only the economies of Chile, French Guiana, and Brazil had a positive impact on trade openness; these economies are characterized by their better performance in the economic complexity index, their higher percentage of budget for research and development expenses, and their trade policies oriented towards the industrialization of their value-added products.</span></p>
Phased T2T 1KGP panel - code and performance data
<p>This repository contains all code and resources required to reproduce the panels and figures published as part of "A T2T-CHM13 recombination map and globally diverse haplotype reference panel improves phasing and imputation".</p> <p>phasing_T2T_data.tar.gz contains a series of parquet files that together contain all dataframes generated when evaluating this panel.</p> <p> </p> <p>This panel is now hosted on AWS as part of the human pangenomics s3 drive at:<br><span><a href="https://s3-us-west-2.amazonaws.com/human-pangenomics/index.html?prefix=T2T/CHM13/assemblies/variants/1000_Genomes_Project/chm13v2.0/Phased_SHAPEIT5_v1.1"><span>https://s3-us-west-2.amazonaws.com/human-pangenomics/index.html?prefix=T2T/CHM13/assemblies/variants/1000_Genomes_Project/chm13v2.0/Phased_SHAPEIT5_v1.1</span></a></span><span> </span></p> <p>The github repository containing more information about this panel is at https://github.com/JosephLalli/phasing_T2T.</p>
Targeted Gene Panel Sequencing Data of RELN paper - Meyer Children's Hospital IRCCS
<h3>Dataset description</h3> <p> </p> <p>The dataset has been prepared according the Minimal Information about a high throughput SEQuencing Experiment (MINSEQE) as reported in: <a href="https://doi.org/10.5281/zenodo.5706412">https://doi.org/10.5281/zenodo.5706412</a></p> <p>This dataset includes:</p> <ul> <li>The Targeted Gene Panel Sequencing Raw Data (FASTQ files) from two individuals harbouring RELN variants</li> <li>The ‘final’ processed data, submitted both as VCF and TXT files, and obtained from the ANNOVAR annotations of the two patients</li> </ul> <p>The gene panel list used in the targeted capture and the essential experimental and data processing protocols has been reported in the RELN paper.</p> <h3>Identifiers</h3> <p>The 444D indentifier correspond to <strong>DN1 patient</strong> in the RELN paper.</p> <p>Tissue: peripheral blood sample</p> <p>Sex: female</p> <p>Age at sequencing: 21 years</p> <p>The 528T indentifier correspond to <strong>DN2 patient </strong>in the RELN paper.</p> <p>Tissue: peripheral blood sample</p> <p>Sex: female</p> <p>Age at sequencing: 1.5 years</p>
Impact of public health expenditure on malnutrition among Peruvians during the period 2010-2020: A panel data analysis
<p><strong><span>Background: </span></strong><a name="_Hlk170909708"></a><span>The study analyzes the impact of public health spending on malnutrition among Peruvians, using data from the National Household Survey, the Central Reserve Bank of Peru, the National Institute of Statistics and Informatics and the Ministry of Economy and Finance from 2010. -2020. Previous studies have revealed the existing relationship of health spending with the reduction of malnutrition</span><span>.</span></p> <p><strong><span>Methods:</span></strong><span> A quantitative approach is considered, with an explanatory type of research using panel data methodology considering the bidimensionality of the data, which allows quantifying this effect for the Peruvian case using the National Household Survey, data from the Central Reserve Bank of Peru, as well as information from the National Institute of Statistics and Informatics and the</span><strong><span> </span></strong><span>Transparency Portal of the Ministry of Economy and Finance in the period 2010-2020.</span><strong><span> </span></strong></p> <p><strong><span>Results: </span></strong><span>The results show that public expenditure on health has a negative relationship with malnutrition; the rural sector has a positive relationship with malnutrition given the limitations present for access to adequate food. Similarly, the unemployment rate shows a positive relationship with malnutrition, given that being unemployed leads to a higher cause of malnutrition in the population, and the gross domestic product has a negative relationship with malnutrition, given that greater economic growth produces an impact on reducing malnutrition, with the greatest impact being on the rural population and the gross domestic product. </span></p> <p><strong><span>Conclusions:</span></strong><span> In the analysis period 2010-2020 in Peru, based on the panel data analysis, the impact of public health expenditure on reducing malnutrition is observed in 10 departments, achieving a reduction in malnutrition; while in 14 departments, this indicator has not been reduced.</span></p>
Measured BSDF and data-driven model of a laser cut panel (LCP001)
<p>Model generated from the measured Bidirectional Scattering Distribution Function (BSDF) of a LCP. The RADIANCE tool-chain pabopto2bsdf, bsdf2ttree was employed. Initial tensor resolution set to 128x128 incident, and equal number of outgoing, scattered directions (corresponding to approx. 1.4 degree). Subsequent adaptive data reduction by approx. 98%. Photometric BSDF.</p> <p>The measured data is included as Differential Scattering Function (DSF): DSF = BSDF x cos(theta_s), where theta_s is the off-normal angle of the outgoing, scattered direction of light (the first column in the measured data). The data was measured on a scanning gonio-photometer (pab advanced technologies pgII) at the optical laboratory of CC Building Envelopes. A halogen lamp was employed, focud on the detector plane for maximum resolution, with a hot-mirror installed in the illuminator to block near infrared emission. The Si photocell of the detector was equipped with a weighing filter to match photometric response v(lambda). The profiles through the unobstructed beam are given for the phi=0°,180°, and phi=90°,270° planes.</p> <p>The angular coordinates theta=90, phi=0 correspond to the intended up direction when installed vertically, e.g. in a window.</p> <p>When publishing any work making use of this data-set, please reference either this data-set, including its Digital Object Identifier (DOI:<a href="https://doi.org/10.5281/zenodo.3375294">10.5281/zenodo.3375294</a>), or (preferred) by this article which describes sample, model and its exemplary application:</p> <p>Lars Oliver Grobe. Photon mapping in image-based visual comfort assessments with BSDF models of high resolution. Journal of Building Performance Simulation. DOI:10.1080/19401493.2019.1653994</p>
Data from: The impact of aid sanctions on maternal and child mortality, 1990–2019: A panel analysis
Open the record for dataset details and reuse information.
Data from: One panel to rule them all: DArTcap genotyping for population structure, historical demography, and kinship analyses, and its application to a threatened shark
With recent advances in sequencing technology, genomic data are changing how important conservation management decisions are made. Applications such as Close-Kin Mark-Recapture demand large amounts of data to estimate population size and structure, and their full potential can only be realised through ongoing improvements in genotyping strategies. Here we introduce DArTcap, a cost-efficient method that combines DArTseq and sequence capture, and illustrate its use in a high resolution population analysis of Glyphis garricki, a rare, poorly known and threatened euryhaline shark. Clustering analyses and spatial distribution of kin pairs from four different regions across northern Australia and one in Papua New Guinea, representing its entire known range, revealed that each region hosts at least one distinct population. Further structuring is likely within Van Diemen Gulf, the region that included the most rivers sampled, suggesting additional population structuring would be found if other rivers were sampled. Coalescent analyses and spatially explicit modelling suggest that G. garricki experienced a recent range expansion during the opening of the Gulf of Carpentaria following the conclusion of the Last Glacial Maximum. The low migration rates between neighbouring populations of a species that is found only in restricted coastal and riverine habitats show the importance of managing each population separately, including careful monitoring of local and remote anthropogenic activities that may affect their environments. Overall we demonstrated how a carefully chosen SNP panel combined with DArTcap can provide highly accurate kinship inference and also support population structure and historical demography analyses, therefore maximising cost-effectiveness.
Data from: RapidRat: development, validation and application of a genotyping-by-sequencing panel for rapid biosecurity and invasive species management
<p>Invasive alien species (IAS) are among the main causes of global biodiversity loss. Invasive brown (Rattus norvegicus) and black (R. rattus) rats, in particular, are leading drivers of extinction on islands, especially in the case of seabirds where >50% of all extinctions have been attributed to rat predation. Eradication is the primary form of invasive rat management, yet this strategy has resulted in a ~10-38% failure rate on islands globally. Genetic tools can help inform IAS management, but such applications to date have been largely reactive, time-consuming, and costly. Here, we developed a Genotyping-in-Thousands by sequencing (GT-seq) panel for rapid species identification and population assignment of invasive brown and black rats (RapidRat) in Haida Gwaii, an archipelago comprising ~150 islands off the central coast of British Columbia, Canada. We constructed an optimized panel of 443 single nucleotide polymorphisms (SNPs) using previously generated double-digest restriction-site associated DNA (ddRAD) genotypic data (27,686 SNPs) from brown (n=295) and black rats (n=241) sampled throughout Haida Gwaii. The informativeness of this panel for identifying individuals to species and island of origin was validated relative to the ddRAD results; in all comparisons, admixture coefficients and population assignments estimated using RapidRat were consistent. To demonstrate application, 20 individuals from novel invasions of three islands (Agglomerate, Hotspring, Ramsay) were genotyped using RapidRat, all of which were confidently assigned (>98.5% probability) to Faraday and Murchison Islands as putative source populations. These results indicated that a previous eradication on Hotspring Island was conducted at an inappropriate geographic scale; future management should expand the eradication unit to include neighboring islands to prevent re-invasion. Overall, we demonstrated that RapidRat is an effective tool for managing invasive rat populations in Haida Gwaii and provided a clear framework for GT-seq panel development for informing biodiversity conservation in other systems.</p>
Solar panels and solar farms in the UK - geographic open data (UKPVGeo)
<p>We present the results of a major crowd-sourcing campaign to create open geographic data for over 260,000 solar PV installations across the UK, covering the vast majority of the capacity in the country. We focus in particular on capturing small-scale domestic solar PV, which accounts for a significant fraction of generation but was until now very poorly documented.</p> <p>The data we introduce will enable decarbonisation at national scales, through forecasting and management of generation, and also serves as a training dataset for machine vision detection of new PV.</p> <p>For a complete description please see <a href="https://www.nature.com/articles/s41597-020-00739-0">the research paper describing the dataset</a>. Please cite this paper in any academic use of the data.</p>
Data from: Validation of grain yield QTL from soft winter wheat using a CIMMYT spring wheat panel
Validation of quantitative trait loci (QTLs) is an essential step in marker-assisted breeding. The objectives of this study were to validate grain yield (GY) QTLs previously identified in soft red winter wheat (Triticum aestivum L.) through biparental and association mapping using the spring wheat association mapping initiative (WAMI) panel from CIMMYT, Mexico, and to identify allele combinations of the validated QTLs that resulted to the highest GY. Linked single-nucleotide polymorphisms for IWA3560 (3A), IWA1818 (4B), and IWA755 (6B) were significantly associated (P < 0.001) with GY, grain number, and thousand-grain weight in the WAMI. Lines possessing the favorable allele for the QTL at the 3A, 4B, and 6B loci (ACG allele combination) validated on the WAMI had the highest mean GY at 4.55 t ha−1, but three other haplotypes (ACA, GCA, and GCG) differing by one or two alleles in the validated QTL regions were not significantly different. These results validate GY QTLs across winter and spring wheat through genome-wide association analysis and further demonstrate the potential for pyramiding favorable alleles for the genetic improvement of wheat breeding populations.
Data from: multi-level determinants of land use land cover change in Tigray, Ethiopia: a mixed-effects approach using socioeconomic panel and satellite data
<p>The dataset contains six files from three data sources: (1) the Ethiopia Rural Socioeconomic Survey (ERSS)/Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA), a three-round panel data for Ethiopia, filtered for Tigray region; (2) an ERSS follow-up survey on the beliefs and opinions of respondents on land use change conducted in August 2019 in Tigray; and (3) land cover transition data derived from LandSat satellite imagery for years 1986 and 2016. The files include data on household and plot features, prices of land use outputs, a diagonal block matrix of variables for mixed effects analysis, beliefs and opinions on land use change, and land cover transitions. The dataset covers 34 Enumeration Areas (EA) of the ERSS/LSMS-ISA and is representative of the region. It can be useful for studies on land use policies, environmental protection, and the drivers and impacts of land use land cover change in Tigray, Ethiopia. The data were processed using user-written codes in STATA v.17.</p>
Data for: Information accessibility, accounting manipulation, and sustainable development of digital enterprises: Based on double moderating effect model and panel PSM-DID method
<p>A theoretical mechanism was analyzed from the micro perspective of the enterprise to explore how information accessibility moderates the effect of accounting manipulation on the sustainable development of digital enterprises. Using data from 1200 listing digital enterprises in China and the DEA-Malmquist index method, the efficiency value of digital enterprises in 2007–2021 was estimated to represent the index of sustainable development of digital enterprises. The accounting manipulation was detected using the panel PSM-DID method based on the Administrative Measures for the Recognition of High-tech Enterprise's policy. The information accessibility value was estimated based on the MDA method. Empirical studies were conducted using text analysis, the panel PSM-DID method, and the double moderating effect model. The results showed that: (1) Accounting manipulation had a negative impact on the sustainable development of "true" digital enterprises and the "fake" digital enterprises; (2) Information accessibility directly and positively enhanced the technological progress and scale efficiency of digital enterprises, and its moderating effect was heterogeneous, with a significant moderating effect on the "true" digital enterprises and a negative effect on the "fake" ones.</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.