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179 results for “data matrix”
Data from: Examining the full effects of landscape heterogeneity on spatial genetic variation: a multiple matrix regression approach for quantifying geographic and ecological isolation
Understanding the effects of landscape heterogeneity on spatial genetic variation is a primary goal of landscape genetics. Ecological and geographic variables can contribute to genetic structure through geographic isolation, in which geographic barriers and distances restrict gene flow, and ecological isolation, in which gene flow among populations inhabiting different environments is limited by selection against dispersers moving between them. Although methods have been developed to study geographic isolation in detail, ecological isolation has received much less attention, partly because disentangling the effects of these mechanisms is inherently difficult. Here, I describe a novel approach for quantifying the effects of geographic and ecological isolation using multiple matrix regression with randomization. I explored the parameter space over which this method is effective using a series of individual-based simulations and found that it accurately describes the effects of geographic and ecological isolation over a wide range of conditions. I also applied this method to a set of real-world datasets to show that ecological isolation is an often overlooked but important contributor to patterns of spatial genetic variation and to demonstrate how this analysis can provide new insights into how landscapes contribute to the evolution of genetic variation in nature.
Data from: MonotomidGen – A matrix-based interactive key to the New World genera of Monotomidae (Coleoptera, Cucujoidea)
A matrix-based Lucid key is presented for the twelve genera of Monotomidae (Coleoptera: Cucujoidea) represented in the New World. A general overview is given for the features and technical specifications of an original interactive key for the identification of these genera. The list of terminal taxa included with the key provides a current summary of monotomid generic diversity for the Nearctic and Neotropical regions.
Data from: Matrix type and landscape attributes modulate avian taxonomic and functional spillover across habitat boundaries in the Brazilian Atlantic Forest
Land use intensification drives biodiversity loss worldwide. In heterogeneous landscape mosaics, both overall forest area and anthropogenic matrix structure induce changes in biological communities in primary habitat remnants. However, community changes via cross-habitat spillover processes along forest-matrix interfaces remain poorly understood. Moreover, information on how landscape attributes affect spillover processes across habitat boundaries are embryonic. Here, we quantify avian and β-diversity (as proxies of spillover rates) across two dominant types of forest-matrix interfaces (forest-pasture and forest-eucalyptus plantation) within the Atlantic Forest biodiversity hotspot in southeast Brazil. We also assess the effects of anthropogenic matrix type and landscape attributes (forest cover, edge density and land-use diversity) on bird taxonomic and functional β-diversity across forest-matrix boundaries. Alpha taxonomic richness was higher in forest edges than within both matrix types, but between matrix types, it was higher in pastures than in eucalyptus plantations. Although significantly higher in forests edges than in the adjacent eucalyptus, bird functional richness did not differ between forest edges and adjacent pastures. Community changes (β-diversity) related to species and functional replacements (turnover component) were higher across forest-pasture boundaries, whereas changes related to species and functional loss (nested component) were higher across forest-eucalyptus boundaries. Forest edges adjacent to eucalyptus had significant higher species and functional replacements than forest edges adjacent to pastures. Forest cover negatively influenced functional β-diversity across both forest-pasture and forest-eucalyptus interfaces. We show the importance of matrix type and the structure of surrounding landscapes (mainly forest cover) on rates of bird assemblage spillover across forest-matrix boundaries, which has profound implications to biological fluxes, ecosystem functioning and land-use management in human-modified landscapes.
Data from: The role of species traits in mediating functional recovery during matrix restoration
Reversing anthropogenic impacts on habitat structure is frequently successful through restoration, but the mechanisms linking habitat change, community reassembly and recovery of ecosystem functioning remain unknown. We test for the influence of edge effects and matrix habitat restoration on the reassembly of dung beetle communities and consequent recovery of dung removal rates across tropical forest edges. Using path modelling, we disentangle the relative importance of community-weighted trait means and functional trait dispersion from total biomass effects on rates of dung removal. Community trait composition and biomass of dung beetle communities responded divergently to edge effects and matrix habitat restoration, yielding opposing effects on dung removal. However, functional dispersion—used in this study as a measure of niche complementarity—did not explain a significant amount of variation in dung removal rates across habitat edges. Instead, we demonstrate that the path to functional recovery of these altered ecosystems depends on the trait-mean composition of reassembling communities, over and above purely biomass-dependent processes that would be expected under neutral theory. These results suggest that any ability to manage functional recovery of ecosystems during habitat restoration will demand knowledge of species' roles in ecosystem processes.
Data from: Pollinator-mediated gene flow connects green roof populations across the urban matrix: a paternity analysis of the self-compatible forb Penstemon hirsutus
Gene flow between populations can help maintain genetic diversity and prevent inbreeding, which is especially important for small, fragmented habitats. Many plant species rely on pollinators to move pollen between populations. In urban areas, insufficient pollinator services may result in limited gene flow, which can have negative consequences such as genetic drift and inbreeding depression. Furthermore, restored populations that are established with few founders of low genetic diversity may have limited long-term population persistence. Here, we tested the hypotheses that populations of a self-compatible forb established on urban green roofs fromnursery stock are genetically depauperate and that limited gene (pollen) flow between populations will result in increased inbreeding. We compared the neutral genetic diversity of Penstemon hirsutus, using nine microsatellite loci, between three green roof populations established from nursery stock and three natural populations. We also established ten experimental populations on green roofs and measured rates of outcrossing and inbreeding and identified the movement of pollen within and between roofs using a paternity analysis. We found that neutral genetic diversity of populations established from nursery stock was lower than that of natural populations, although the level of inbreeding was also lower on the green roofs. In our experimental populations, we found that the rates of outcrossing and inbreeding varied between the roof populations. Our results suggest that inbreeding may be correlated with cover of co-flowering species but not with any of the other measured site properties. The location of likely pollen donors suggested that on average, 75% of pollen was derived from plants within the population (including self) and 25% came from plants on different roofs. Our results document realized pollen movement within and between green roofs, demonstrating that these habitats provide important connectivity in a fragmented environment.
Data from: Nest boxes increase reproductive output for Tree Swallows in a forest grassland matrix in central British Columbia
Secondary cavity-nesting birds depend on tree cavities for nesting and roosting, but many studies of these birds are conducted using nest boxes. Implementation of effective conservation strategies for cavity-nesting species such as nest-site supplementation requires careful comparisons of fecundity and other vital rates for birds using both natural and artificial nest site types. We compared breeding phenology, clutch and brood sizes, and fledging success of Tree Swallows (Tachycineta bicolor) nesting in tree cavities and nest boxes during 2001–2003 in British Columbia, Canada. Swallows using nest boxes initiated egg-laying and hatched young at approximately the same time as those in tree cavities (2 June, 23 June, respectively). Female Tree Swallows in boxes laid larger clutches (5.9 ± 0.9 eggs, N = 76) than those in tree cavities (4.2 ± 1.6 eggs, N = 67). The mean number of nestlings hatched was greater in nest boxes (5.2 ± 1.1 nestlings, N = 67) than in tree cavities (2.6 ± 2.0 nestlings, N = 58). Pairs in boxes were over twice as successful in producing fledglings (93.4%; 57 of 61 pairs fledged > 1 young) than those in tree cavities (35.8%; 19 of 53 pairs). Of those successful nests, pairs nesting in boxes fledged 5.1 ± 1.1 young (N = 57), whereas those in tree cavities fledged 3.5 ± 1.2 young (N = 18). Because cavities in nest boxes averaged 60% larger in volume and 1.8 cm wider internally than tree cavities, we suggest that increased reproductive output was correlated with boxes enabling a larger clutch size. In previous research, we found that Tree Swallows were a poor competitor with other cavity-nesting passerines for tree cavities. The addition of nest boxes may serve as an effective way to supplement local reproduction for secondary cavity-nesting bird populations by reducing competition for limited nest sites. This is especially true in regions where the availability of natural nesting sites is highly variable, and where species compete with many other cavity-nesting passerines using a similar ecological niche and nesting cavities.
Data from: Spectral diversity area relationships for assessing biodiversity in a wildland-agriculture matrix
Species-area relationships have long been used to assess patterns of species diversity across scales. Here this concept is extended to spectral diversity using hyperspectral data collected by NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over western Michigan. This mixture of mesic forest and agricultural lands offers two end-points on the local-scale diversity continuum – one set of well mixed forest patches and one set of highly homogeneous agricultural patches. Using the sum of the first three principal component values and the principal components' convex hull volume, spectral diversity was compared within and among these plots and to null expectations for perfectly random and perfectly patchy landscapes. Overall the spectral diversity area relationship confirms the patterns that would be expected for this landscape, but this application suggests that this approach could be extended to less well understood landscapes and could reveal key insights about the relative importance of different drivers of community assembly, even in the absence of additional data about plant functional traits or species' identities.
Data from: The B-matrix harbours significant and sex-specific constraints on the evolution of multi-character sexual dimorphism
The extent to which sexual dimorphism can evolve within a population depends on an interaction between sexually divergent selection and constraints imposed by a genetic architecture that is shared between males and females. The degree of constraint within a population is normally inferred from the intersexual genetic correlation, rmf. However, such bivariate correlations ignore the potential constraining effect of genetic covariances between other sexually co-expressed traits. Using the fruit fly Drosophila serrata, a species that exhibits mutual mate preference for blends of homologous contact pheromones, we tested the impact of between-sex between-trait genetic covariances using an extended version of the genetic variance-covariance matrix, G, that includes Lande's (1980) between-sex covariance matrix, B. We find that including B greatly reduces the degree to which male and female traits are predicted to diverge in the face of divergent phenotypic selection. However, the degree to which B alters the response to selection differs between the sexes. The overall rate of male trait evolution is predicted to decline, but its direction remains relatively unchanged, whereas the opposite is found in females. We emphasise the importance of considering the B-matrix in microevolutionary studies of constraints on the evolution of sexual dimorphism.
Data from: Similarity in G matrix structure among natural populations of Arabidopsis lyrata
Understanding the stability of the G matrix in natural populations is fundamental for predicting evolutionary trajectories, yet, the extent of its spatial variation and how this impacts responses to selection remain open questions. With a nested paternal half-sib crossing design and plants grown in a field experiment, we examined differences in the genetic architecture of flowering time, floral display and plant size among four Scandinavian populations of Arabidopsis lyrata. Using a multivariate Bayesian framework, we compared the size, shape and orientation of G matrices and assessed their potential to facilitate or constrain trait evolution. Flowering time, floral display and rosette size varied among populations and significant additive genetic variation within populations indicated potential to evolve in response to selection. Yet, some characters, including flowering start and number of flowers, may not evolve independently because of genetic correlations. Using a multivariate framework, we found few differences in the genetic architecture of traits among populations. G matrices varied mostly in size rather than shape or orientation. Differences in multivariate responses to selection predicted from differences in G were small, suggesting overall matrix similarity and shared constraints to trait evolution among populations.
Pressure-induced amorphisation and a new high density amorphous metallic phase in matrix-free Ge nanoparticles: simulation data
<p>The folder contains:</p> <p>-Pseudopotential files for Ge and H in the .recpot format used in all calculations.</p> <p>-Input and output files for constant enthalpy geometry relaxations of hydrogenated Ge nanocrystals using the electronic enthalpy method within ONETEP (version 3.3).</p> <p>-Input and output files for the DFPT calculations performed with CASTEP (version 6.01).</p>
NetCDF data matrix with Lagrangian dispersal simulation output
<p>zipped NetCDF file (unzipped ~444GB)</p> <p>The NetCDF file contains a data matrix with the number of particles per bin (lon 0.015°, lat 0.01°) in the geographic area from -12°W - 10°E, and 47°N - 63°N.<br>Particle numbers are labelled according to the three simulated scenarios ("period" 0-2, 14-28, 0-28 days after release), by station ("station" as named in stations.csv)", by year ("year" 2019-2022), and by day when the simulation was started ("offset", 000-122 days counting from 01.05.-31.08.)</p> <p>data variable: <br>particle_number [111,007,858,176 values, float32]</p> <p>dimensions: <br>lon_bin [length 1468, float32]<br>lat_bin [length 1601, float32]<br>period [length 3, object '0-2','14-28','0-28']<br>station [length 32, object 'DK_044','FR_0206'....(all station names)]<br>year [length 4, object '2019'...'2022']<br>offset [length 123, object '000'...'122']</p>
Data from: Can matrix structure affect animal navigation between fragments? A dispersal experiment using release platforms
<p>The persistence of species in fragmented landscapes relies on landscape connectivity and individuals' ability in dispersing among habitat patches. Accordingly, matrix structure can affect the orientation of dispersing individuals across the landscape. In this study, we measured the impact of matrix structure on the dispersal performance of the white-eared opossum (Didelphis albiventris). We released individuals in three types of matrix: bare field, corn crops and soybean crops, with distances of 30, 50 and 100 m to the nearest habitat patch. To test if the release height would affect the individuals' dispersal performance, we released animals from the ground and from 2 m high platforms. We released and tracked 14 individuals in bare field on the ground; 30 in corn crops, 22 on the ground and 8 on platforms; 17 on soybeans crop, 12 on the ground and 5 on platforms. The type of matrix influenced the perceptual range. Perceptual range was 100 m in bare field, 50 m in cornfield and less than 30 m in soybean field. The platforms only increased the perceptual range of individuals in the cornfield from 50 to 100 m. Visual and olfactory cues would cause this effect. We conclude that matrix structure affects dispersal performance, and that vertical elements of the matrix, such as scattered trees, may increase orientation in crop fields during inter-patch dispersal.</p>
Indonesian soil and litter Collembola species and trait matrix with environmental data
<p>Rainforest conversion and expansion of plantations in tropical regions is associated with changes in animal communities and biodiversity decline. In soil, Collembola are one of the most numerous invertebrate groups that control microbial processes and support arthropod predators. Despite that, information on the impact of changes in land use in the tropics on species and trait composition of Collembola communities is very limited. We investigated the response of Collembola to the conversion of rainforest into rubber agroforest ('junge rubber'), rubber and oil palm plantations in Jambi province (Sumatra, Indonesia), a region that experienced one of the strongest deforestation globally during the last decades. Collembola from litter and soil layers were collected in 2013 and 2016 using heat extraction. In the litter layer, density and species richness in plantation systems declined by 25-38% and 30-40%, respectively, compared to rainforest. By contrast, in the soil layer, density, species richness and trait diversity of Collembola were only slightly affected by land-use change contrasting the response of many other animal groups. Species and trait composition of Collembola communities in litter and soil layers differed between all land-use systems. Water content and pH were identified as main factors related to the differences in species and trait composition both in litter and soil layers, followed by the density of micro- and macropredators. Dominant Collembola species in rainforest and jungle rubber were characterized by small body size, absence of furca and absent or intense pigmentation, while in plantations larger species with long furca and diffuse or patterned coloration were more abundant. The trait-based responses were similar to those observed in Collembola from temperate regions and to those in a similar study on spiders at our study sites. Overall, land-use change negatively affected Collembola communities in the litter layer, but only little affected Collembola communities in soil. Several pantropical Collembola genera (i.e., <i>Isotomiella</i>, <i>Pseudosinella</i> and <i>Folsomides</i>) dominated across land-use systems, reflecting their high environmental adaptability or efficient dispersal calling for studies on their ecology and genetic diversity. The decline in species richness and density of litter-dwelling Collembola with the conversion of rainforest into plantation systems calls for management practices mitigating negative effects of the deterioration of the litter layer in rubber but in particular in oil palm plantations.</p>
Data for Performance-Portable Solid Mechanics via Matrix-Free p-Multigrid
<p>Data, scripts to make the figures, and tex source for the paper: https://arxiv.org/abs/2204.01722</p>
Data from: Improvement of genomic predictions in small breeds by construction of genomic relationship matrix through variable selection
<p>Genomic selection has been increasingly implemented in the animal breeding industry, and it is becoming a routine method in many livestock breeding contexts. However, its use is still limited in several small-population local breeds, which are, nonetheless, an important source of genetic variability of great economic value. A major roadblock for their genomic selection is accuracy when population size is limited: to improve breeding value accuracy, variable selection models that assume heterogenous variance have been proposed over the last few years. However, while these models might outperform traditional and genomic predictions in terms of accuracy, they also carry a proportional increase of breeding value bias and dispersion. These mutual increases are especially striking when genomic selection is performed with a low number of phenotypes and high shrinkage value—which is precisely the situation that happens with small local breeds. In our study, we tested several alternative methods to improve the accuracy of genomic selection in a small population. First, we investigated the impact of using only a subset of informative markers regarding prediction accuracy, bias, and dispersion. We used different algorithms to select them, such as recursive feature eliminations, penalized regression, and XGBoost. We compared our results with the predictions of pedigree-based BLUP, single-step genomic BLUP, and weighted single-step genomic BLUP in different simulated populations obtained by combining various parameters in terms of number of QTLs and effective population size. We also investigated these approaches on a real data set belonging to the small local Rendena breed. Our results show that the accuracy of GBLUP in small-sized populations increased when performed with SNPs selected via variable selection methods both in simulated and real data sets. In addition, the use of variable selection models—especially those using XGBoost—in our real data set did not impact bias and the dispersion of estimated breeding values. We have discussed possible explanations for our results and how our study can help estimate breeding values for future genomic selection in small breeds.</p>
Data for 'Noninvasive megapixel fluorescence microscopy through scattering layers by a virtual reflection-matrix'
<p>This repository hosts the datasets used in the study 'Noninvasive megapixel fluorescence microscopy through scattering layers by a virtual reflection-matrix.' It includes sets of images of fluorescent samples positioned behind a scattering layer, captured using random illuminations in a microscope setup detailed in the paper. The data correspond to the examples and figures presented in the publication.</p>
Data of Rosenbrock method of "A unifying framework for ADI-like methods for linear matrix equations and beneficial consequences"
<p>This deposit contains the datasets generated by the Rosenbrock method for the paper:</p> <ul> <li>J. Schulze, J. Saak: "A unifying framework for ADI-like methods for linear matrix equations and beneficial consequences".</li> </ul> <p>Download the individual files and store them inside the directory <code>data/rosenbrock/</code>.</p> <p>The file names are structured as follows.</p> <ul> <li><code>Rail5177</code>: <a href="https://morwiki.mpi-magdeburg.mpg.de/morwiki/index.php/Steel_Profile">Steel Profile</a> benchmark problem of dimension 5177</li> <li><code>adi_initprev=true|false</code>: whether the initial ADI iterate was set to the solution at the previous time step (or zero)</li> <li><code>adi_kwargs=...</code>: keyword arguments passed to ADI method <ul> <li><code>maxiters=200</code>: maximum number of iterations</li> <li><code>reltol=1e-10</code>: relative tolerance to reason about convergence</li> <li><code>shifts=...</code>: shift strategy</li> </ul> </li> <li><code>nsteps=45|150</code>: number of Rosenbrock steps</li> <li><code>tspan=(4500.0, 0.0)</code>: global time span of DRE</li> <li><code>.jld2</code>: file suffix. All file have been generated with <a href="https://github.com/JuliaIO/JLD2.jl">JLD2.jl</a> version 0.4.38</li> </ul> <p>Load the dataset via <code>using JLD2</code> and <code>file = load(FILENAME)</code>. This will yield a dictionary having the following entries:</p> <ul> <li><code>file["rosenbrock_metrics"]</code>: data frame containing execution metrics of Rosenbrock iterations</li> <li><code>file["adi_metrics"]</code>: data frame containing execution metrocs of ADI iterations of all Rosenbrock iterations</li> <li><code>file["timer"]</code>: isolated runtime metrics generated with <a href="https://github.com/KristofferC/TimerOutputs.jl">TimerOutputs.jl</a> version 0.5.23</li> <li><code>file["timer_metrics"]</code>: runtime metrics of seperate run with additional data observers enabled</li> <li><code>file["config"]</code>: internal configuration object that led to this dataset (information also embedded in file name)</li> <li><code>file["failed"]</code>: Boolean on whether configuration has failed (always <code>false</code>) </li> </ul> <p>All data frames were generated with <a href="https://github.com/JuliaData/DataFrames.jl">DataFrames.jl</a> version 1.6.1 and have their columns documented <a href="https://dataframes.juliadata.org/stable/lib/metadata/">using metadata</a>.</p> <p>Generating this dataset took ~22h and consumed ~2.72kWh of electricity.</p>
Data of Newton method of "A unifying framework for ADI-like methods for linear matrix equations and beneficial consequences"
<p>This deposit contains the datasets generated by the Newton method for the paper:</p> <ul> <li>J. Schulze, J. Saak: "A unifying framework for ADI-like methods for linear matrix equations and beneficial consequences".</li> </ul> <p>Download the individual files and store them inside the directory <code>data/newton-adi/</code>.</p> <p>The file names are structured as follows.</p> <ul> <li><code>Rail5177</code>: <a href="https://morwiki.mpi-magdeburg.mpg.de/morwiki/index.php/Steel_Profile">Steel Profile</a> benchmark problem of dimension 5177</li> <li><code>adi_initprev=true|false</code>: whether the initial ADI iterate was set to the solution of the previous Newton step (or zero)</li> <li><code>adi_kwargs=...</code>: keyword arguments passed to ADI method <ul> <li><code>maxiters=1000</code>: maximum number of iterations</li> <li><code>shifts=...</code>: shift strategy</li> </ul> </li> <li><code>newton_kwargs=...</code>: keyword arguments passed to Newton method <ul> <li><code>inexact=true|false</code>: whether to use inexact Newton method</li> <li><code>inexact_hybrid=true|false</code>: whether to switch back to classical Newton method in later iterations (only present if <code>inexact=true</code>)</li> <li><code>linesearch=true|false</code>: whether to employ line search</li> <li><code>reltol=1e-10</code>: relative tolerance to reason about convergence</li> </ul> </li> <li><code>β=1000</code>: scaling of the quadratic term in the ARE</li> <li><code>.jld2</code>: file suffix. All file have been generated with <a href="https://github.com/JuliaIO/JLD2.jl">JLD2.jl</a> version 0.4.38</li> </ul> <p>Load the dataset via <code>using JLD2</code> and <code>file = load(FILENAME)</code>. This will yield a dictionary having the following entries:</p> <ul> <li><code>file["newton_metrics"]</code>: data frame containing execution metrics of Newton iterations</li> <li><code>file["adi_metrics"]</code>: data frame containing execution metrocs of ADI iterations of all Newton iterations</li> <li><code>file["timer"]</code>: isolated runtime metrics generated with <a href="https://github.com/KristofferC/TimerOutputs.jl">TimerOutputs.jl</a> version 0.5.23</li> <li><code>file["timer_metrics"]</code>: runtime metrics of seperate run with additional data observers enabled</li> <li><code>file["config"]</code>: internal configuration object that led to this dataset (information also embedded in file name)</li> <li><code>file["failed"]</code>: Boolean on whether configuration has failed</li> </ul> <p>All data frames were generated with <a href="https://github.com/JuliaData/DataFrames.jl">DataFrames.jl</a> version 1.6.1 and have their columns documented <a href="https://dataframes.juliadata.org/stable/lib/metadata/">using metadata</a>.</p> <p>Generating this dataset took ~3h and consumed ~0.25kWh of electricity.</p>
Data matrix for generating co-mentioning circle
<p>data used in </p> <p>Nielsen, T., Pettersson, M., Toft, L., Lindemann, D. M., & Nielsen, E. H. (2024). Development and Initial Validation of the Practice Self-Efficacy Questionnaire (PSEQ) for Student Teachers. <em>Educational Methods & Psychometrics.</em></p>
Experimental Data for 'Beyond memory-effect matrix-based imaging in scattering media by acousto-optic gating'
<p>This repository contains the data used in Figures 3 and 4 of our study on noninvasive imaging beyond the optical memory-effect utilizing acousto-optic gating. The data files are organized into two folders: 'Figure 3' and 'Figure 4'. All data files can be loaded using PyTorch.</p> <p><strong>Folder Structure and Content:</strong></p> <ol> <li> <p><strong>Figure 3:</strong></p> <ul> <li>This folder contains the measurements that have been digitally propagated to the conjugated plane.</li> <li>The folder also includes a ground truth file named 'object_direct_imaging.trc'.</li> </ul> </li> <li> <p><strong>Figure 4:</strong></p> <ul> <li>This folder contains two data files: <ul> <li>One file includes measurements with acoustic modulation.</li> <li>The other file includes measurements without acoustic modulation.</li> </ul> </li> <li>The folder also contains a ground truth file named 'digits_direct_imaging.trc'.</li> </ul> </li> </ol> <p> </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.