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12,393 results for “materiality”
Out-of-plane ferroelectricity and robust magnetoelectricity in quasi two-dimensional materials
<p>Thin film ferroelectrics have been pursued for capacitive and nonvolatile memory devices. They rely on polarizations that are oriented in an out-of-plane direction to facilitate integration and addressability with CMOS architectures. The internal depolarization field, however, formed by surface charges can suppress the out-of-plane polarization in ultrathin ferroelectric films that could otherwise exhibit lower coercive fields and operate with lower power. Here we unveil stabilization of a polar longitudinal optical (LO) mode in the <em>n</em>=2 Ruddlesden–Popper family that produces out-of-plane ferroelectricity, persists under open-circuit boundary conditions, and is distinct from hyperferroelectricity. Our first-principles calculations show the stabilization of the LO mode is ubiquitous in chalcogenides and halides and relies on anharmonic trilinear mode coupling. We further show that the out-of-plane ferroelectricity can be predicted with a crystallographic tolerance factor, and we use these insights to design a room-temperature multiferroic with strong magnetoelectric coupling suitable for magneto-electric spin-orbit transistors. </p>
The Double-Edged Sword Of Diversity: How Diversity, Conflict, and Psychological Safety Impacts Software Teams: Dataset and Supplementary Materials
<p>This bundle contains supplementary materials for an upcoming academic publication The Double-Edged Sword Of Diversity: How Diversity, Conflict, and Psychological Safety Impacts Software Teams, by Christiaan Verwijs and Daniel Russo. Included in the bundle are the dataset, SPSS syntaxes, and model definitions (AMOS). This replication package is made available by C. Verwijs under a "Creative Commons Attribution Non-Commercial Share-Alike 4.0 International"-license (CC-BY-NC-SA 4.0).</p><p><strong>About the dataset</strong></p><p>The dataset (SPSS) contains anonymized response data from 1.118 respondents aggregated into 161 (Agile) software teams that participated from the <a href="https://scrumteamsurvey.org">https://scrumteamsurvey.org</a>. Data was gathered between September 2021, and January 2022. We cleaned the individual response data from careless responses and removed all data that could potentially identify teams, individuals, or their parent organizations. Because we wanted to analyze our measures at the team level, we calculated a team-level mean for each item in the survey. Such aggregation is only justified when at least 10% of the variance exists at the team level (Hair, 2019), which was the case (ICC = 35-45%). No data was missing on the team level.</p><p>The dataset contains question labels and answer option definitions. To conform to the privacy statement of [scrumteamsurvey.org](https://scrumteamsurvey.org), the bundle does not include response data from before the team-level aggregation.</p><p><strong>About the model definitions</strong></p><p>The bundle includes definitions for Structural Equation Models (SEM) for AMOS. We added the iterations of the measurement model, four models used to perform a test for common method bias, and the path model that includes interactions. Indirect effects were calculated with the <a href="http://statwiki.gaskination.com/index.php?title=CFA">"Indirect Effects" plugin</a> for AMOS by James Gaskin.</p><p><strong>About the SPSS syntaxes</strong></p><p>The bundle includes the syntaxes we used to prepare the dataset from the raw import, as well as the syntax we used to generate descriptives. This is mostly there for other researchers to verify our procedure.</p>
Supplementary material for "Analyzing potential niche shifts in alien pairs of mantis species (Insecta, Mantodea), with comments on the current taxonomic and ecological knowledge"
<p>###Supplementary data for "Analyzing potential niche shifts in alien pairs of mantis species (Insecta, Mantodea), with comments on the current taxonomic and ecological knowledge"</p><p>angui_intra: intra-species analyses for <i>Tenodera angustipennis</i>, with both complete and trimmed dataset.</p><p>contrhierodula: intra-species analyses for the <i>Hierodula</i> species with controversial status (<i>H. transcaucasica</i>/<i>H. tenuidentata</i>). It includes analyses between <i>H. transcaucasica</i> and <i>H. tenuidentata sensu stricto</i> and the populations treated as separated species.</p><p>hierodula_europe: inter-species analysis with the two <i>Hierodula</i> present in Europe.</p><p>kendall: scripts and table used for calculating Kendall's rank correlation.</p><p>pate_intra: intra-species analyses for <i>Hierodula patellifera</i>, with both complete and trimmed (no India, Nepal and Philippines points) datasets. There is also the analyses between Asian distribution and India, Nepal and Philippines points</p><p>sinensis_intra: intra-species analyses for <i>Tenodera sinesis</i>, with both complete and trimmed datasets.</p><p>tenodera_europe: inter-species analysis with the two <i>Tenodera</i> present in North America, with both complete and trimmed datasets.</p><p>####NOTE</p><p>I did not include the raw presence points (the elaborated ones are together with the values in a csv file per each folder) and the wordlclim variables. For the latter, you can get them from the WorldClim website. If you want the raw presence points, I will give them on request</p><p>WARNING: AN ITALIAN LOCALE HAS BEEN USED FOR THIS ANALYSES; IF YOU HAVE ANY FORMAT ISSUE WITH THE CSV, CONSIDER USING THIS FOR IMPORTING INTO R:<br><br>read_csv("namefile.csv", locale = locale(decimal_mark = ",", grouping_mark = "."))</p><p> </p><p>IF THAT DOES NOT WORK, PLEASE CONTACT ME</p>
Alevin in commandline - Galaxy Training Material
<p>Input datasets for Generating a single cell matrix using Alevin (bash + R) tutorial on Galaxy Training Network. </p>
Datasets of VAMAS TWA2 Project 33: Chemical characterization of graphene related two-dimensional materials by XPS
<p>The datasets contain excel-files of the XPS raw data of the participants of the interlaboratory comparison. Additionally, the protocol is added.</p>
CRAFTED: An exploratory database of simulated adsorption isotherms of nanoporous materials
<p><strong>Overview</strong></p><p>The files in this repository compose the <strong>C</strong>harge-dependent, <strong>R</strong>eproducible, <strong>A</strong>ccessible, <strong>F</strong>orcefield-dependent, and <strong>T</strong>emperature-dependent <strong>E</strong>xploratory <strong>D</strong>atabase (<strong>CRAFTED</strong>) of adsorption isotherms. This dataset contains the simulation of CO2 and N2 adsorption isotherms on 690 metal-organic frameworks taken from the CoRE-MOF-2014 database and 667 covalent organic frameworks taken from the CURATED-COFs database. The simulations were performed with two force fields (UFF and DREIDING), six partial charge schemes (no charges, Qeq, EQeq, DDEC, MPNN, and PACMOF), and three temperatures (273, 298, 323 K).</p><p><strong>Contents</strong></p><ul><li>CIF_FILES/ contains 6 folders (NEUTRAL, DDEC, EQeq, Qeq, MPNN, and PACMOF), each one with 1357 CIF files;</li><li>FORCEFIELDS/ contains 2 folders (UFF and DREIDING) with the definition of the forcefields;</li><li>INPUT_FILES/ contains 97,704 input files for the GCMC simulations;</li><li>ISOTHERM_FILES/ contains 97,704 adsorption isotherms resulting from the GCMC simulation;</li><li>ENTHALPY_FILES/ contains 97,704 enthalpies of adsorption from the isotherms;</li><li>RAC_DBSCAN/ contains the RAC and geometrical descriptors to perform the t-NSE + DBSCAN analysis;</li></ul><p><strong>Licenses</strong></p><p>The 690 MOF-related CIF files in the DDEC folder were downloaded from <a href="https://doi.org/10.5281/zenodo.3986573">CoRE-MOF-2014</a> and are licensed under the terms of the Creative Commons Attribution 4.0 International license (<a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a>). The 667 COF-related CIF files in the NEUTRAL folder were downloaded from <a href="https://github.com/danieleongari/CURATED-COFs">CURATED-COFs</a> and are licensed under the terms of the MIT license (<a href="https://github.com/danieleongari/CURATED-COFs/blob/master/LICENSE">MIT</a>).</p><blockquote><p>Dalar Nazarian, Jeffrey S. Camp, & David S. Sholl. (2016). Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2014 DDEC Database [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.3986573">https://doi.org/10.5281/zenodo.3986573</a></p><p>Ongari, Daniele, et al. "Building a consistent and reproducible database for adsorption evaluation in covalent–organic frameworks." ACS Central Science 5.10 (2019): 1663-1675. <a href="https://doi.org/10.1021/acscentsci.9b00619">https://doi.org/10.1021/acscentsci.9b00619</a></p><p>Ongari, Daniele, Leopold Talirz, and Berend Smit. "Too many materials and too many applications: An experimental problem waiting for a computational solution." ACS Central Science 6.11 (2020): 1890-1900. <a href="https://doi.org/10.1021/acscentsci.0c00988">https://doi.org/10.1021/acscentsci.0c00988</a></p></blockquote><p>The CO2.def and N2.def forcefield files were downloaded from <a href="https://github.com/iRASPA/RASPA2/tree/master/molecules/ExampleDefinitions">RASPA</a> and are licensed under the terms of the <a href="https://github.com/iRASPA/RASPA2/blob/master/COPYING">MIT</a> license.</p><blockquote><p>Dubbeldam, David, et al. "RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials." Molecular Simulation 42.2 (2016): 81-101. <a href="https://doi.org/10.1080/08927022.2015.1010082">https://doi.org/10.1080/08927022.2015.1010082</a></p></blockquote><p>The remaining MOF-related CIF files in the PACMOF, MPNN, Qeq, EQeq and NEUTRAL folders were derived from those in the DDEC folder and are licensed under the terms of the Creative Commons Attribution 4.0 International license (<a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a>) from the CoRE-MOF-2014 subset. The remaining COF-related CIF files in the PACMOF, MPNN, Qeq, EQeq and DDEC folders were derived from those in the NEUTRAL folder and are licensed under the terms of the MIT license (<a href="https://github.com/danieleongari/CURATED-COFs/blob/master/LICENSE">MIT</a>) from the CURATED-COFs subset.</p><p>All remaining files were created by us, and are licensed under the terms of the <a href="https://cdla.dev/sharing-1-0/">CDLA-Sharing-1.0</a> license.</p><p><strong>Software requirements</strong></p><p>In order to create a Python environment capable of running the Jupyter notebooks, please install <a href="https://docs.conda.io/en/latest/miniconda.html">conda</a> and execute</p><p>conda env create --file environment.yml</p><p><strong>Usage instructions</strong></p><p>Execute the command below to run JupyterLab in the appropriate Python environment.</p><p>conda run --name crafted jupyter-lab</p><p> </p>
3D Printed Living Bacterial Cellulose and Biopolymer Composite Material Samples
<p>The images in this dataset were captured during an experiment initiated on 13 March 2023 at CITA, at the Royal Danish Academy, School of Architecture. The experiment was performed on 3d printed samples made from a material combining living cellulose-producing bacteria with a biopolymer composite. The biopolymer composite combines a xantham gum binder, glycerol and calcium chloride with cellulose fillers sourced from side and waste streams materials. During the experiment, the dormant bacterial cellulose was reawakened through the spraying of tea nutrient at timed intervals of 30 minutes for 2 seconds, for a period of 42 days.</p><p> </p>
Using Old Laboratory Equipment with Modern Web-of-Things Standards: a Smart Laboratory with LabThings Retro. Supplementary material - Video demonstration
<p>Supplementary Material for 'Using Old Laboratory Equipment with Modern Web-of-Things Standards: a Smart Laboratory with LabThings Retro'. </p><p>Video demonstration for LabThings Retro. </p><p>This video has no sound.</p>
NorSand4AI: A Comprehensive Triaxial Test Simulation Database for NorSand Constitutive Model Materials
<p>Dataset of the homonymous paper: a first-of-its-kind database that addresses the size and complexity issues of creating synthetic datasets for nonlinear constitutive modeling of soils by simulating both drained and undrained triaxial tests. Two datasets are provided: the first one considers a nested Latin Hypercube Sampling of input parameters encompassing 2000 soil types, each subjected to 40 initial test configurations, resulting in a total of 160000 triaxial test results (NorSandTXL_H5.zip). The second one considers nested quasi-Monte Carlos sampling techniques (Sobol and Halton) of input parameters encompassing 2048 soil types, each subjected to 42 initial test configurations, resulting in a total of 172032 triaxial test results (NorSand_2048_42_Drained.zip and NorSand_2048_42_Undrained.zip). Each simulation dataset comprises a 4000 by 10 matrix that can be used for general multivariate forecasting benchmarks, in addition to direct geotechnical and soil science applications.</p>
Supplementary material for: Phylogenetic biodiversity metrics should account for both accumulation and attrition of evolutionary heritage
<p>Phylogenetic metrics are essential tools used in the study of ecology, evolution and conservation. Phylogenetic diversity (PD) in particular is one of the most prominent measures of biodiversity, and is based on the idea that biological features accumulate along the edges of phylogenetic trees that are summed. We argue that PD and many other phylogenetic biodiversity metrics fail to capture an essential process that we term attrition. Attrition is the gradual loss of features and other sources of variety through causes other than extinction. Here we introduce `EvoHeritage', a generalisation of PD that is founded on the joint processes of accumulation and attrition of features. We argue that whilst PD measures evolutionary history, EvoHeritage is required to capture a more pertinent subset of evolutionary history including only components that have survived attrition. We show that EvoHeritage is not the same as PD on a tree with scaled edges; instead, accumulation and attrition interact in a more complex non-monophyletic way that cannot be captured by edge lengths alone. This leads us to speculate that the one-dimensional edge lengths of classic trees may be insufficiently flexible to capture the nuances of evolutionary processes. We derive a measure of EvoHeritage and show that it elegantly reproduces species richness and PD at opposite ends of a continuum based on the intensity of attrition. We demonstrate the utility of EvoHeritage in ecology as a predictor of community productivity compared with species richness and PD. We also show how EvoHeritage can quantify living fossils and resolve their associated controversy. We suggest how the existing calculus of PD-based metrics and other phylogenetic biodiversity metrics can and should be recast in terms of EvoHeritage accumulation and attrition.</p>
Mapping and modelling global mobility infrastructure stocks, material flows and their embodied greenhouse gas emissions - Data
<p>Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures. </p><p>The data in this repository show the material stocks contained in global mobility infrastructure networks at the country-level and mapped at 5arcmins, as well as country-level estimates of material flows for maintenance, replacement and expansion of those infrastructures, and the associated GHG emissions from materials production. This repository contains all data as shown in figures of the article, including the GeoTIFF files for figure 3, and the supplementary data file containing full country-level results.</p><p><strong>Data</strong><br>This dataset includes the following data:</p><ul><li>Global maps of material stocks in mobility infrastructure networks at 5 arcmins, separate for all roads, all rail-based infrastructure, as well as in total and per capita</li><li>Global country-level material stock estimates for mobility infrastructures</li><li>Global country-level estimates of material flows and associated GHG emissions for materials production</li><li>Material intensity in mass per area of road (kg/m²) per road type</li><li>Material intensity in mass per area of railway track (kg/m²) per railway type</li><li>Material intensity in mass per area (kg/m²) per bridges and tunnels</li></ul><p>Material intensity factors are available for iron and steel, concrete, asphalt, aggregate (sand & gravel), timber, and other.</p><p><strong>Further information</strong><br>This dataset complements the following scientific article:</p><p>Wiedenhofer, Dominik, André Baumgart, Sarah Matej, Doris Virág, Gerald Kalt, Maud Lanau, Danielle Densley Tingley, u. a. "Mapping and Modelling Global Mobility Infrastructure Stocks, Material Flows and Their Embodied Greenhouse Gas Emissions". <i>Journal of Cleaner Production</i>, November 2023, 139742. <a href="https://doi.org/10.1016/j.jclepro.2023.139742">https://doi.org/10.1016/j.jclepro.2023.139742</a>.</p><p>For further information please see the publication. You can also contact Dominik Wiedenhofer <a href="mailto:dominik.wiedenhofer@boku.ac.at">dominik.wiedenhofer(a)boku.ac.at</a> and visit our <a href="https://boku.ac.at/understanding-the-role-of-material-stock-patterns-for-the-transformation-to-a-sustainable-society-mat-stocks">website</a> to learn more about our project: <i>MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.</i></p><p><strong>Funding</strong><br>This research was funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). </p>
Supplementary Material for "Diversity, evolution, and classification of the RNA-guided nucleases TnpB and Cas12"
<p>Data and files for "Diversity, evolution, and classification of the RNA-guided nucleases TnpB and Cas12" as described in the SI Appendix. </p>
Lost in translation: A historical-comparative reconstruction of Proto-Khoe-Kwadi based on archival data - Supplementary Material
<p>Supplementary Materials 1-4 for the following article: </p><p>Fehn, Anne-Maria & Jorge Rocha. 2023. Lost in translation: A historical-comparative reconstruction of Proto-Khoe-Kwadi based on archival data. Diachronica. https://doi.org/10.1075/dia.23022.feh.</p>
Data and analysis scripts: Evidence supporting an evolutionary trade-off between material properties and architectural design in Anolis lizard long bones
<p>In biology, 'many-to-one mapping' occurs when multiple morphological forms can meet a particular functional demand. Knowledge of this mapping is crucial for understanding how selection on performance shapes the evolution of morphological diversity. Past research has focused primarily on the potential for geometrically alternative morphological designs to produce equivalent performance outcomes. Here we ask whether the material properties of biological tissues hold similar potential. Through phylogenetic comparative study of <em>Anolis</em> lizards, we show that the architectural design and mineral density of the femur trade off in a many-to-one functional system, yielding a morphospace featuring parallel isolines in size-relative bending strength. Anole femur evolution has largely tracked a narrow band of strength isolines over phylogenetic timescales, suggesting that geometry and mineral content shape the course of macroevolution through compensatory effects on performance. Despite this conserved evolutionary relationship, insular and continental species evolve strong bones differently, likely reflecting underlying ecological differences. Mainland anoles, which exhibit fast-paced life histories, typically have femora with lower mineralization and thinner walls than island species, which exhibit the opposite strategy. Together, our results reveal an overlooked dimension in the relationship between form and function, expanding our understanding of how many-to-one mapping can shape patterns of phenotypic diversity.</p>
Material suplementario - Análisis de la productividad, colaboración e impacto de la educación en el deporte (1999-2018)
<p>Dataset in a xlsx file used by Joan Aleixandre-Agulló in the research "Análisis de la productividad, colaboración e impacto de la educación en el deporte (1999-2018)".</p>
Experimental raw data sets associated with certified reference material BAM-P116 (titanium dioxide) for comparison of nitrogen and argon sorption, available in the universal adsorption information format (AIF)
<p>These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.<br>The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.<br>It is recommended to use the following requirements for the molecular cross-sectional area:<br>Nitrogen: 0.1620 nm²<br>Argon: 0.1420 nm²</p> <p>Expected specific surface area for nitrogen (BET): 305 to 345 m²/g<br>Expected specific surface area for argon (BET): 300 to 310 m²/g</p> <p>Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.<br>The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.<br>These data are stored in the universal AIF format (adsorption information format), which allows flexible use of the data.</p>
Supplementary material for "Does sociality affect evolutionary speed?"
<p>This supplementary material contains Table 1 which summarises all evidence discussed throughout the paper and used to create Figure 3 in Socias-Martínez and Peckre (2023) Does sociality affect evolutionary speed?, Peer Community Journal, 3: XX. <a href="https://doi.org/10.24072/pcjournal.352">https://doi.org/10.24072/pcjournal.352</a>.</p>
Dataset for "Effect of benzothiadiazole-based π-spacers on fine-tuning of optoelectronic properties of oligothiophene-core donor materials for efficient organic solar cells: a DFT study"
<p># Data and code for "Effect of benzothiadiazole-based π-spacers on fine-tuning of optoelectronic properties of oligothiophene-core donor materials for efficient organic solar cells: a DFT study."</p><p>## Contents</p><p>* data-{type}/*: reproducible data</p><p>* job.job : example slurm script</p><p> </p><p>## Description of the data</p><p>The data are organized in subdirectories *data-{type}/{system}/* corresponding to the considered molecules and simulation type:</p><p>* data-gs: Ground state calculations</p><p>* data-td: TD-DFT calculations</p><p>The contents of each subdirectory are:</p><p>* data-gs/{system}/structure.xyz: physical atomic structure</p><p>* data-td/{system}/td-dft/td_uvvis.txt: photoabsorption spectrum</p><p>The spectrum plots in the article correspond to the first (x values) and second (y values) columns of the spectrum files.</p><p> </p><p>## Reproduction of the data</p><p>The data were produced using Gaussian version g16.A.01</p><p>The calculation of the data of a system consists of the following steps:</p><p>1. Ground-state (gs) calculation:</p><p> * Prepare the input file for the gs by adjusting the parameters of the ground state calculations:</p><p> * "# opt b3lyp/6-311+g(d,p) scrf=(smd,solvent=chloroform) geom=connectivity empiricaldispersion=gd3bj out=wfn"</p><p> * out = wfn keyword to create a wfn file of the ground state that will be used for EDD and RDG investigations</p><p> * Submit the job.job file for the gs calculation as appropriate for the particular input file of the system</p><p> * The optimized sturctures are visualised using GaussView</p><p>2. Time-propagation calculation:</p><p> * Requires finished ground-state calculation</p><p> * Set up the TD-DFT calculation parameters as necessary:</p><p> * "# td=(nstates=6) wb97xd/6-311+g(d,p) scrf=(smd,solvent=chloroform) guess=read density out=wfn"</p><p> * density out = wfn keywords to create a wfn file of the excited state that will be used for EDD investigation</p><p> * Submit the job.job file for TD-DFT calculation as appropriate for the particular system</p><p> * The photoabsoption specta are visualised using GaussView</p><p>3. RDG calculation:</p><p> * Put the .wfn file of the gs calculation in the command window of the open source Multiwfn software and follow the sturcture in Section 3.23.1 in the manual</p><p>4. DOS calculation:</p><p> * The dos curves are plotted starting from the .fchk of the ground state geometry, select the atoms index corresponding to the diffrents subpart of the studied molecules (donor, acceptor, pi-spacer)</p><p> * Put the .fchk file of the gs calculation in the command window of the open source Multiwfn software and follow the structure in Section 4.10.1 in the manual</p><p> * the output generates .chk file which is transformed to .fchk file : formchk .chk .fch</p><p>5. TDM calculations:</p><p> * Requires finished ground-state calculation</p><p> * Set up the TD-DFT calculaton parameters as necessary</p><p> * "# td=(nstates=6) wb97xd/6-311+g(d,p) scrf=(smd,solvent=chloroform) guess=read density transition=1 iop(6/8=3) out=wfn"</p><p> * Put the .fchk file of the gs calculation in the command window of the open source Multiwfn software and follow the sturcture in Section 4.18.8 in the manual</p><p>6. EDD calculation:</p><p> * Edd plots are plotted based on the es.wfn and gs.wfn following Section 4.18.1 in the manual</p><p> </p>
Label-free imaging of DNA interactions with 2D materials
<p>Raw images and data analysis related to the manuscript entitled "Label-free imaging of DNA interactions with 2D materials"</p>
Test results from quasi-static impact tests over SMC materials reinforced with glass fibre (ramdom and textile)
<p>Test results from quasi-static impact tests over SMC materials with structural properties conceived for automotive applications, reinforced with glass fibre (samples with ramdom distribution of fibres and samples reinforced with GF textile)</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.