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Data from: AgMate: an optimal mating software versus other mate pair designing methods on long-term breeding of Pinus taeda L
<p>Breeding objectives aim to optimize two crucial but contrasting goals of maximizing genetic gain while managing genetic diversity. In advanced generations, this becomes a challenge in monoecious conifer tree species breeding programs because they suffer from inbreeding. Developing an algorithm that maximizes genetic gain while maintaining genetic diversity for monoecious species is imperative. While methods and algorithms for animal breeding are well-established, an efficient algorithm suited to monoecious species remains elusive. Towards this goal, we have adopted an evolutionary genetic algorithm, the Differential Evolution algorithm, to optimize mate pair designing in <em>Pinus taeda</em> (loblolly pine), a widely planted pine species in the southern USA. AgMate, an optimal mating for monoecious species software, is a multi-functional, completely automated optimization software. It utilizes genetic relationships and breeding values as input to create an optimal mating list. AgMate maximizes the genetic gain and minimizes the increase in average coancestry and inbreeding in the proposed progeny. AgMate was more effective in optimizing mating lists than positive assortative mating and random mating in short-term and long-term settings. AgMate mating list resulted in an average 93% genetic gain each cycle for ten cycles while simultaneously minimizing the increase in coancestry to 0.086. The framework and methods adapted for Pinus taeda are also relevant to the breeding of other monoecious species.</p>
Global Long-term River Width (GLOW)
<p>This repository archives the Global LOng term river Width (GLOW) dataset measured from Landsat for 1984-2020.</p> <p>There are three datasets in this repository: Width, Cross_section, and Environmental_parameter_global.</p> <p>Width contains the GLOW dataset, which has three attributes: ID, date (mm/dd/yyyy), and width (unit: meters). Each cross-section is identified by a unique ID in the format of R########XS#######. The dataset is grouped into eight regions based on the geospatial location.</p> <p>Cross-section contains the shapefiles indicating the GLOW cross-section locations, which have three attributes: ID, lat (latitude), and lon (longitude).</p> <p>Environmental_parameter_global contains the environmental parameters generated in this study for the Random Forest analysis, which has eighteen parameters for all global rivers at the river reach level, including the temporal trend slope, interquartile range, 25th percentile, and 75th percentile of air temperature, snowmelt, precipitation, evapotranspiration, and river discharge. </p> <p> </p> <p>Please refer to the following paper for more details:</p> <p>Feng, D., Gleason C.J., Yang X., Allen G.H., and Pavelsky T.M., How have global river widths changed over time? Water Resources Research </p> <p> </p>
Long-term observation of the egg and chick size in the nests of Larus ichthyaetus in Lake Chany,West Siberia, Russia
<p>Data on long-term observation and morphological study of the eggs of the great black-headed gull<em> Larus ichthyaetus </em>in the nesting colonies of gulls on islands of Lake Chany. Russia. Data on long-term observation and morphological study of the eggs (Data S1) and chick (Data S2) of the great black-headed gull<em> Larus ichthyaetus </em>in the nesting colonies of gulls on islands of Lake Chany, Russia</p> <p> </p> <p><strong>Abstract </strong></p> <p>This data set describes the long-term observation and morphological study of the eggs of the great black-headed gull Larus ichthyaetus in the gull nesting colonies on the islands of Lake Chany. Lake Chany is located in the Baraba forest-steppe of the West Siberian Plain, Russia, between the Ob and Irtish rivers. Lake Chany is protected by the Ramsar Convention on the Wetlands of International Importance, indicating that the lake is an important site for migratory birds, including L. ichthyaetus. This dataset contains the size and fate of all eggs, as well as the size of hatched chicks in 1164 observed L. ichthyaetus nests from 1993 to 2003.</p>
Data and R code for long-term study of fire and climate effects on water quality in Clear Lake, California
<p>Long-term relationships between water quality, fire and climate for Clear Lake, California. Although the watershed has historically experienced frequent fire, the 2018 Mendocino Complex, which was the largest wildfire complex in state history, burned approximately 40% of the watershed, sparking concerns about drinking water quality and lake ecosystem health. This analysis spans approximately 1968-2021.</p>
Code and Data associated with "Idiosyncratic purifying selection on metabolic enzymes in the long-term evolution experiment with Escherichia coli"
<p>Code and data sufficient to reproduce analyses in "Idiosyncratic purifying selection on metabolic enzymes in the long-term evolution experiment with <em>Escherichia coli</em>".</p>
Long-term experimental drought alters floral scent and pollinator visits in a Mediterranean plant community despite overall limited impacts on plant phenotype and reproduction
<p>Pollinators are declining globally, with climate change implicated as an important driver. Climate change can induce phenological shifts and reduce floral resources for pollinators, but little is known about its effects on floral attractiveness and how this might cascade to affect pollinators, pollination functions and plant fitness. We used an in situ long-term drought experiment to investigate multiple impacts of reduced precipitation in a natural Mediterranean shrubland, a habitat where climate change is predicted to increase the frequency and intensity of droughts. Focusing on three insect-pollinated plant species that provide abundant rewards and support a diversity of pollinators (<em>Cistus</em> <em>albidus</em>, <em>Salvia</em> <em>rosmarinus</em> and <em>Thymus</em> <em>vulgaris</em>), we investigated the effects of drought on a suite of floral traits including nectar production and floral scent. We also measured the impact of reduced rainfall on pollinator visits, fruit set and germination in <em>S</em>. <em>rosmarinus</em> and <em>C</em>. <em>albidus</em>. Drought altered floral emissions of all three plant species qualitatively, and reduced nectar production in <em>T</em>. <em>vulgaris</em> only. <em>Apis</em> <em>mellifera</em> and <em>Bombus</em> gr. <em>terrestris</em> visited more flowers in control plots than drought plots, while small wild bees visited more flowers in drought plots than control plots. Pollinator species richness did not differ significantly between treatments. Fruit set and seed set in <em>S. rosmarinus</em> and <em>C. albidus </em>did not differ significantly between control and drought plots, but seeds from drought plots had slower germination for <em>S. rosmarinus</em> and marginally lower germination success in <em>C. albidus</em>.</p> <p><em>Synthesis</em>. Overall, we found limited but consistent impacts of a moderate experimental drought on floral phenotype, plant reproduction and pollinator visits. Increased aridity under climate change is predicted to be stronger than the level assessed in the present study. Drought impacts will likely be stronger and this could profoundly affect the structure and functioning of plant-pollinator networks in Mediterranean ecosystems.</p>
Data for: "Dynamic species distribution modeling reveals the pivotal role of human-mediated long-distance dispersal in plant invasion"
<p>All the data needed to reproduce the results and Figures of our article:</p> <p>Botella, C., Bonnet, P., Hui, C., Joly, A., & Richardson, D. M. (2022). Dynamic Species Distribution Modeling Reveals the Pivotal Role of Human-Mediated Long-Distance Dispersal in Plant Invasion. <em>Biology</em>, <em>11</em>(9), 1293. <a href="https://doi.org/10.3390/biology11091293">https://doi.org/10.3390/biology11091293</a></p> <p>Please, find the R scripts and guidelines to reproduce our results on the article's Github repository :</p> <p><a href="https://github.com/ChrisBotella/plectranthus_barbatus/tree/main">https://github.com/ChrisBotella/plectranthus_barbatus/tree/main</a></p>
LRGB: Long Range Graph Benchmark
<p>Graph Neural Networks (GNNs) that are based on the message passing (MP) paradigm exchange information between 1-hop neighbors to build node representations at each layer. In principle, such networks are not able to capture long-range interactions (LRI) that may be desired or necessary for learning a given task on graphs. Recently, there has been an increasing interest in development of Transformer-based methods for graphs that can consider full node connectivity beyond the original sparse structure, thus enabling the modeling of LRI. However, MP-GNNs that simply rely on 1-hop message passing often fare better in several existing graph benchmarks when combined with positional feature representations, among other innovations, hence limiting the perceived utility and ranking of Transformer-like architectures. Here, we present the Long Range Graph Benchmark (LRGB) with 5 graph learning datasets: PascalVOC-SP, COCO-SP, PCQM-Contact, Peptides-func and Peptides-struct that arguably require LRI reasoning to achieve strong performance in a given task. We benchmark both baseline GNNs and Graph Transformer networks to verify that the models which capture long-range dependencies perform significantly better on these tasks. Therefore, these datasets are suitable for benchmarking and exploration of MP-GNNs and Graph Transformer architectures that are intended to capture LRI.</p> <p><a href="https://arxiv.org/abs/2206.08164">arXiv</a>, <a href="https://paperswithcode.com/paper/long-range-graph-benchmark">Papers with Code</a></p>
Long-Term Lithium Abundance Signatures following Planetary Engulfment [Dataset]
<p>MESA inlist files and chemical network used for the published article Sevilla et. al (2022).</p> <p>The inlist files given are for a 1 solar mass model. To generate the other models in the paper with a different stellar mass, the initial mass in the pre-ZAMS inlist was changed.</p> <p>We first used prezams.inlist to generate the model star, with mixing processes besides convection. This model saved after this run would be used for all other model runs for the same stellar mass.</p> <p>For a model run without planetary engulfment, we used one inlist to evolve the star through the main-sequence, and then obtained the desired data from the resulting profile and history files.</p> <p>For model runs with planetary engulfment, we first ran the model using an accretion inlist to simulate the engulfment process by turning on accretion, and then we used a main-sequence (MS) inlist to evolve the star through the main-sequence to produce the desired data.</p> <p>The corresponding inlists for each model run are as follows:</p> <p>10 Earth mass engulfment with included all mixing processes considered in our paper, which were convection, overshoot, thermohaline mixing, elemental diffusion, and a min_D_mix coefficient: 10earth_accretion.inlist for accretion, and 10earth_postaccretion.inlist for MS.</p> <p>10 Earth mass engulfment with all mixing processes except thermohaline mixing: 10earth_accretion_nothermohaline.inlist for accretion, and 10earth_postaccretion_nothermohaline.inlist for MS.</p> <p>10 Earth mass engulfment with all mixing processes except elemental diffusion: 10earth_accretion_nodiffusion.inlist for accretion, and 10earth_postaccretion_nodiffusion.inlist for MS.</p> <p>1 Earth mass engulfment with all mixing processes: 1earth_accretion.inlist for accretion, and 1earth_postaccretion.inlist for MS.</p> <p>100 Earth mass engulfment with all mixing processes: 100earth_accretion.inlist for accretion, and 100earth_postaccretion.inlist for MS.</p> <p>10 Earth mass engulfment with all mixing processes occurring 1 gyr after ZAMS: We first ran the model with evolve_1gyr.inlist to save a model of the star 1 gyr after ZAMS. Then, we used 1gyr_accretion.inlist for accretion, and 1gyr_postaccretion.inlist for MS.</p> <p>No planetary engulfment: No accretion inlist was used; we immediately ran no_accrete.inlist as the MS inlist.</p> <p> </p> <p>We also uploaded the chemical network used for our model as the file accrete.net.</p>
The evolution, complexity and diversity of models of long-term forest dynamics
<p><span>1. To assess the impacts of climate change on vegetation from stand to global scales, models of forest dynamics that include tree demography are needed. Such models are now available for 50 years, but the currently existing diversity of model formulations and its evolution over time are poorly documented. This hampers systematic assessments of structural uncertainties in model-based studies.</span></p> <p><span>2. We conducted a meta-analysis of 28 models, focusing on models that were used in the past five years for climate change studies. We defined 52 model attributes in five groups (basic assumptions, growth, regeneration, mortality and soil moisture) and characterized each model according to these attributes. Analyses of model complexity and diversity included hierarchical cluster analysis and redundancy analysis.</span></p> <p><span>3. Model complexity evolved considerably over the past 50 years. Increases in complexity were largest for growth processes, while complexity of modelled establishment processes increased only moderately. Model diversity was lowest at the global scale, and highest at the landscape scale. We identified five distinct clusters of models, ranging from very simple models to models where specific attribute groups are rendered in a complex manner and models that feature high complexity across all attributes.</span></p> <p><span>4. Most models in use today are not balanced in the level of complexity with which they represent different processes. This is the result of different model purposes, but also reflects legacies in model code, modelers' preferences, and the 'prevailing spirit of the epoch'. The lack of firm theories, laws and 'first principles' in ecology provides high degrees of freedom in model development, but also results in high responsibilities for model developers and the need for rigorous model evaluation.</span></p> <p><span>5. Synthesis. The currently available model diversity is beneficial: convergence in simulations of structurally different models indicates robust projections, while convergence of similar models may convey a false sense of certainty. The existing model diversity – with the exception of global models – can be exploited for improved projections based on multiple models. We strongly recommend balanced further developments of forest models that should particularly focus on establishment and mortality processes, in order to provide robust information for decisions in ecosystem management and policymaking.</span></p>
Parent-of-origin detection and chromosome-scale haplotyping using long-read DNA methylation sequencing and Strand-seq
<p>Hundreds of loci in human genomes have alleles that are methylated differentially according to their parent of origin. These imprinted loci generally show little variation across tissues, individuals, and populations. We show that such loci can be used to distinguish the maternal and paternal homologs for all autosomes, without the need for the parental DNA. We integrate methylation-detecting nanopore sequencing with the long-range phase information in Strand-seq data to determine the parent of origin of chromosome-length haplotypes for both DNA sequence and DNA methylation in five trios with diverse genetic backgrounds.</p>
Long-term (2001-2020) global full-coverage daytime and nighttime carbon monoxide profile and total column
<p>Validation results are in preparation. The full dataset will be uploaded after the submission/acceptance of our paper.</p>
Long-Term, Single-Molecule Imaging of Proteins in Live Cells with Photoregulated Fluxional Fluorophores
<p>Supporting data for paper "Long-Term, Single-Molecule Imaging of Proteins in Live Cells with Photoregulated Fluxional Fluorophores"</p>
CASM: A long-term Consistent Artificial-intelligence based Soil Moisture dataset based on machine learning and remote sensing
<p>Paper to cite: Skulovich, O., Gentine, P. A Long-term Consistent Artificial Intelligence and Remote Sensing-based Soil Moisture Dataset. <em>Sci Data</em> 10, 154 (2023). https://doi.org/10.1038/s41597-023-02053-x</p> <p> </p> <p>The Consistent Artificial Intelligence (AI)-based Soil Moisture (CASM) dataset is a global, consistent, and long-term, remote sensing soil moisture (SM) dataset created using machine learning. It is based on the NASA Soil Moisture Active Passive (SMAP) satellite mission SM data as a target and is aimed at extrapolating SMAP-like quality SM data back in time with previous satellite microwave platforms. Machine learning approach, such as neural network (NN) has the advantage of being both nonlinear, and state-dependent, and naturally imposing a global distribution matching between the source and the target data. Utilizing this, the new CASM dataset was created using high-quality SMAP SM as a target and Soil Moisture and Ocean Salinity (SMOS) or Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E/2) brightness temperature as a source, which allowed extrapolating SM data 13 years back from before SMAP mission launch. CASM represents SM in the top soil layer, defined on a global 25 km EASE-2 grid and covers 2002-2020 with a 3-day temporal resolution. The resulting dataset exhibits excellent spatial and temporal homogeneity, without compromising the interannual variability, and is in excellent agreement with the SMAP data (with a mean correlation of 0.97 between the SMAP and CASM SM for the period when the two overlap). Moreover, the input and target datasets were divided into seasonal cycle and residuals, with the NN trained on the residuals. This approach ensures that the high performance does not mask a simple seasonal cycle matching but rather exemplifies the skill targeted at predicting extremes; with the NN achieving a correlation of 0.75 on the test data for the residuals. Comparison to 367 global in-situ SM monitoring sites shows a SMAP-like median correlation of 0.66 between station SM and CASM SM from the corresponding grid cell. Additionally, the SM product uncertainty was assessed, and both aleatoric and epistemic uncertainties were estimated and included in the dataset. Mean epistemic uncertainty, related to the NN model structure, ranges from 0.007 m<sup>3</sup>/m<sup>3</sup> to 0.014 m<sup>3</sup>/m<sup>3</sup> and on average is close to a desired SM product stability threshold of 0.01 m<sup>3</sup>/m<sup>3</sup> per year. Aleatoric uncertainty, defined as input noise propagated through the system, depends on the introduced level of noise. With 10% noise applied to the residuals, the resulting mean standard deviation of the model outputs rises from 0.005 to 0.007 m<sup>3</sup>/m<sup>3</sup>. </p>
Data release associated with ``Search for Coincident Gravitational Wave and Long Gamma-Ray Bursts from 4-OGC and the Fermi-GBM/Swift-BAT Catalog"
<p>This is associated data release for the paper https://arxiv.org/abs/2208.03279. It contains the skymaps from potential gravitational-wave candidates from binary neutron star or neutron star-black hole merger. The notebook showcases how to use it. More information can be found in the github repository: https://github.com/gwastro/gw-longgrb</p> <pre> </pre> <pre> </pre>
Global and regional long-term M4.95+ seismicity forecasts undergoing prospective evaluation
<p>Contains a stationary M5.95+ seismicity forecast derived from the Global Earthquake Activity Rate (GEAR1) model of Bird et al. (2015) and nineteen time-invariant M4.95+ earthquake forecasts participating in forecast experiments conducted by the Collaboratory for the Study of Earthquake Predictability (CSEP) in California, New Zealand, and Italy. Ten additional forecast files are included to properly perform comparative tests.</p> <p>Earthquake rates are expressed as number of M4.95+ earthquakes per 0.1<sup>o</sup> cell per year. Forecasts are stored in tab separated values files with the following fields (the first row is shown as an example):</p> <table> <tbody> <tr> <td>lon_min</td> <td>lon_max</td> <td>lat_min</td> <td>lat_1</td> <td>depth_0</td> <td>depth_1</td> <td>mag_0</td> <td>mag_1</td> <td>rate</td> <td>flag</td> </tr> <tr> <td>-125.4</td> <td>-125.3</td> <td>40.1</td> <td>40.2</td> <td>0.0</td> <td>30.0</td> <td>4.95</td> <td>5.05</td> <td>5.8499e-04</td> <td>1</td> </tr> </tbody> </table> <p>The data, forecasts, and tests are described in detail in the following publications and the references contained therein:</p> <p>Bayona, J.A., Savran, W.H., Iturrieta, P., Gerstenberger, M.C., Marzocchi, W., Schorlemmer, D., and Werner, M.J., Are Regionally Calibrated Seismicity Models more Informative than Global Models? Insights from California, New Zealand, and Italy. <em>in review</em>.</p> <p>Bayona, J.A., Savran, W.H., Rhoades, D.A. and Werner, M.J., 2022. Prospective evaluation of multiplicative hybrid earthquake forecasting models in California. <em>Geophysical Journal International</em>, <em>229</em>(3), pp.1736-1753.</p> <p>Bird, P., Jackson, D.D., Kagan, Y.Y., Kreemer, C. and Stein, R.S., 2015. GEAR1: A Global Earthquake Activity Rate Model Constructed from Geodetic Strain Rates and Smoothed SeismicityGEAR1: A Global Earthquake Activity Rate Model Constructed from Geodetic Strain Rates and Smoothed Seismicity. <em>Bulletin of the Seismological Society of America</em>, <em>105</em>(5), pp.2538-2554.</p> <p>Marzocchi W, Schorlemmer D, Wiemer S. Preface. Ann. Geophys. [Internet]. 2010Nov.5 [cited 2022Sep.16];53(3):III-VIII. Available from: https://www.annalsofgeophysics.eu/index.php/annals/article/view/4851</p> <p>Rhoades, D.A., Christophersen, A., Gerstenberger, M.C., Liukis, M., Silva, F., Marzocchi, W., Werner, M.J. and Jordan, T.H., 2018. Highlights from the first ten years of the New Zealand earthquake forecast testing center. <em>Seismological Research Letters</em>, <em>89</em>(4), pp.1229-1237.</p> <p>Savran, W.H., Bayona, J.A., Iturrieta, P., Asim, K.M., Bao, H., Bayliss, K., Herrmann, M., Schorlemmer, D., Maechling, P.J. and Werner, M.J., 2022. pycsep: A python toolkit for earthquake forecast developers. <em>Seismological Society of America</em>, <em>93</em>(5), pp.2858-2870.</p> <p>Schorlemmer, D., Gerstenberger, M.C., Wiemer, S., Jackson, D.D. and Rhoades, D.A., 2007. Earthquake likelihood model testing. <em>Seismological Research Letters</em>, <em>78</em>(1), pp.17-29.</p> <p>Werner, M.J., Zechar, J.D., Marzocchi, W. and Wiemer, S., 2010. Retrospective evaluation of the five-year and ten-year CSEP-Italy earthquake forecasts. <em>arXiv preprint arXiv:1003.1092</em>.</p> <p>Zechar, J.D., Gerstenberger, M.C. and Rhoades, D.A., 2010. Likelihood-based tests for evaluating space–rate–magnitude earthquake forecasts. <em>Bulletin of the Seismological Society of America</em>, <em>100</em>(3), pp.1184-1195.</p> <p>Zechar, J.D., Schorlemmer, D., Werner, M.J., Gerstenberger, M.C., Rhoades, D.A. and Jordan, T.H., 2013. Regional earthquake likelihood models I: First‐order results. <em>Bulletin of the Seismological Society of America</em>, <em>103</em>(2A), pp.787-798.</p>
Can Public Transport Improve Accessibility for the Poor Over the Long Term? Empirical Evidence in Paris, 1968-2010
<p>This dataset allows to reproduce the results of the paper "Can Public Transport Improve Accessibility for the Poor Over the Long Term? Empirical Evidence in Paris, 1968-2010", by Vincent Viguié, Charlotte Liotta, Basile Pfeiffer, and Nicolas Coulombel, submitted to the Journal of Transport Geography and available at SSRN: <a href="https://ssrn.com/abstract=4049765">https://ssrn.com/abstract=4049765</a> or <a href="https://dx.doi.org/10.2139/ssrn.4049765">http://dx.doi.org/10.2139/ssrn.4049765</a>.</p> <p>Files MODUS_private_cars.csv and MODUS_public_transport.csv correspond to the average transport time between municipalities by public transit for the Census years between 1968 and 20109, and by car for the year 2010. MODUS is a model calibrated by the public regional road and transport authority (DRIEAT Île de France) to simulate road traffic and transit in the region. More details can be found in the research paper.</p> <p>Files COM_RES_csp_1968_2010.csv and COM_EMP_csp_1968_2010.csv correspond to the number of employed workers, by place of residence or employment, at the municipality (communes) level, with stable geographical boundaries over time. They are derived from the detailed census of the French population carried out by the INSEE, the French national statistical institute. More details can be found in the research paper.</p>
Code and data used in "A Tool for Air Pollution Scenarios (TAPS v1.0) to enable global, long-term, and flexible study of climate and air quality policies"
<p>Data and code for Tool for Air Pollution Scenarios (TAPS v1.0) as submitted to Geoscientific Model Development for publication. See the enclosed README and full user manual (https://github.com/watkin-mit/TAPS/wiki) for more information. </p>
Fig. 6 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 6. Abundance (mean number of burrows/100 × 5 m transect) of S. citellus in 4 colonies in the study area in summer (for the period 2017–2021) N = Luda Yana; –– l –– = Belotrup; ---- l ---- = Panagyurski kolonii; u = Beli Manastiri
Fig. 5 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 5. Changes in the habitat suitability in the study area (white – not suitable, black – high suitability) of European souslik assessed by maxent modelling based on data from 2006–2018 (B) and extrapolated for the period 1985–2005 (A). The results are presented in
ScienceDex guides
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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.