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10,016 results for “Observation”
Figure Sets and Data Associated with AJ Publication: "NICMOS Kernel-Phase Interferometry I: Catalogue of Brown Dwarfs Observed in F110W and F170M"
<p>Images for Figure Sets 4, 5, 6, 7, and 9 and data behind the figure for Figure 15 from the AJ publication "NICMOS Kernel-Phase Interferometry I: Catalogue of Brown Dwarfs Observed in F110W and F170M" (Currently accepted and in press.). Figure sets and file names are described in the fsREADME file. Data behind the figure is described in the dbfREADME file.</p>
HiPERCAM/ULTRACAM observations of PSR J2051-0827
<p>Optical observations of PSR J2051-0827 taken by the high-speed triple-beam CCD camera ULTRACAM on the William Herschel Telescope, and by the high-speed quintuple-beam CCD camera HiPERCAM on the Gran Telescopio Canarias. As presented in Dhillon et al. 2022 (MNRAS, in press, https://arxiv.org/abs/2208.09249). The letter after the underscore in each file name represents the observing filter for that specific file.</p> <p>For the ULTRACAM data, the columns are:<br> 1) orbital phase (in rotations, with phase = 0 corresponding to pulsar's ascending node),<br> 2) flux density (in erg cm<sup>-2</sup> s<sup>-1</sup> Hz<sup>-1</sup>)<br> 3) flux density uncertainty (in erg cm<sup>-2</sup> s<sup>-1</sup> Hz<sup>-1</sup>)</p> <p>For the HiPERCAM data, the columns are:<br> 1) MJD time<br> 2) orbital phase (in rotations, with phase = 0 corresponding to pulsar's ascending node),<br> 3) flux density (in erg cm<sup>-2</sup> s<sup>-1</sup> Hz<sup>-1</sup>)<br> 4) flux density uncertainty (in erg cm<sup>-2</sup> s<sup>-1</sup> Hz<sup>-1</sup>)</p>
ecochange: An R-package to derive ecosystem change indicators from freely available earth observation products
<p>This release includes the R code necessary to reproduce Figures 2-4 in the Application paper entitled: "ecochange: An R-package to derive ecosystem change indicators from freely available Earth Observation products."</p>
Simulations from "Using Molecular Gas Observations to Guide Initial Conditions for Star Cluster Simulations"
<p>This dataset contains the simulation results from the article "Using Molecular Gas Observations to Guide Initial Conditions for Star Cluster Simulations" (submitted to MNRAS).</p> <p><br> The data is grouped by simulation and by particle type (gas, sinks and stars). Gas is uploaded with one snapshot per 0.05 Myr, sinks and stars with one snapshot per 0.01 Myr. The data is stored in AMUSE data format, which uses hdf5.</p>
Optical polarimetric observations of the black hole binary star Cyg X-1 with RoboPol
<p>The dataset contains raw FITS images of the black hole X-ray binary star <a href="https://simbad.cds.unistra.fr/simbad/sim-id?Ident=%402905066&Name=HD%20226868&submit=submit">Cyg X-1</a>, raw FITS images of a nearby field star used for the interstellar polarization correction and processed measurements of polarimetric standards used for the instrumental polarization correction. The dataset was obtained with the <a href="http://robopol.org">RoboPol</a> optical polarimeter in the R-band mounted at the 1.3 m telescope of the Skinakas Observatory, Greece. The data were collected between 13 May and 1 June 2022.<br> </p>
Data for "Three-Dimensional Broadband Interferometric Mapping and Polarization (BIMAP-3D) Observations of Lightning Discharge Processes" by Shao et al.
<p>Data set for manuscript of “Three-Dimensional Broadband Interferometric Mapping and Polarization (BIMAP-3D) Observations of Lightning Discharge Processes” by Shao et al. submitted to Journal of Geophysical Research-atmosphere</p>
Understanding the heterogeneous rheologic structure across the Longmenshan fault from ten-year postseismic GPS observations
<p>The two datasets are the 10-year cumulative displacements following the 2008 Wenchuan earthquake, GPS time-series observations for all sites, GPS time-series simulation for all sites and the secular velocity corresponding to the interseismic tectonic response, respectively.</p>
White Hole Observation experiment
<p>This set of data is the results from the white hole observation series in parallel to the multispectral data analysis. The <strong>12 - M87 Experiment</strong> with quantum deflection effect have not yet been thoroughly studied nor analyzed.</p>
Atmospheric Distribution of HCN from Satellite Observations and 3-D Model Simulations - TOMCAT data
<p>This repository contains the model data from the paper "Atmospheric Distribution of HCN from Satellite<br> Observations and 3-D Model Simulations" submitted to ACP.</p> <p>The files contains the monthly mean hydrogen cyanide (HCN) mixing ratios modelled using the TOMCAT 3-D offline chemical transport model with a horizontal resolution of 2.8° × 2.8° with 60 hybrid σ-pressure levels from the surface to ~60 km.</p>
Organic Matter and Decomposition Rate Observational Data from Salt Marshes of North Carolina
<p>This data have been collected from salt marshes in Masonboro Island and Wrightsville Beach in NC, US, in 2015 and 2016.</p> <p>The data include organic matter percent, organic carbon percent, bulk density, decomposition rate, stabilization factor, marsh elevation and vegetation cover all along transects from the channel to the inner marsh.</p>
Climate based seed zones for Mexico: spatial grids to guide reforestation under observed and projected climate change
<p>This database entry provides climate-based seed zone system for Mexico to address climate change observed over the last 30 years and projected climate change for the 2050s. The database corresponds to a journal publication by Castellanos-Acuña et al. (2018), available at https://doi.org/10.1007/s11056-017-9620-6. This seed zone classification is based on bands of two climate variables that have often been shown to drive genetic adaptation of tree species: mean coldest month temperature (MCMT), and an aridity index (AHM). MCMT was divided into ten bands of 3°C intervals, with the limits of these bands being, temperatures below <2°C, 2-5°, 5-8°, 8-11°, 11-14°, 14-17°, 17-20°, 20-23°, 23-26°, >26°C. AHM was divided into seven bands with intervals that are approximately equal width under a log-transformation: <20, 20-30, 30-45, 45-65, 65-95, 95-140, and >140 °C/mm. The gridded files provided in this database entry, the classes are coded as integer numbers, with the last digit representing the AHM class (1-7) and the first or first and second digit representing the MCMT class (1-10).</p>
Corresponding Dataset for "Ganymede's Ionosphere observed by a Dual-Frequency Radio Occultation with Juno"
<p> Corresponding Dataset for "Ganymede’s Ionosphere observed <br> by a Dual-Frequency Radio Occultation with Juno"<br> README FILE<br> VERSION 2<br> Dustin Buccino<br> April 22, 2024<br> Jet Propulsion Laboratory<br> California Institute of Technology</p> <p>=============================================================================<br>VERSION 2 INFORMATION<br>=============================================================================</p> <p> Version 2 of this dataset separates the Electron Density profile from the<br>main data files and makes a correction to the egress profile that was<br>discovered. Differences in egress profile are very small and within<br>the uncertainties. Furthermore egress is statistically a non-detection<br>(zero densities), but for sake of accuracy they are reposted to be<br>consistent with the publication.</p> <p>=============================================================================<br>INTRODUCTION<br>=============================================================================</p> <p> This dataset contains processed radio science data and results of the<br>Juno Ganymede radio occultation. This dataset is provided in order to <br>supplement the submitted article to the "Geophysical Research Letters"<br>journal:</p> <p> Buccino, D.R., et al (2022), Ganymede’s Ionosphere observed by a <br> Dual-Frequency Radio Occultation with Juno, Geophysical Research <br> Letters, submitted February 2022.</p> <p><br> Please note the raw data used in this analysis are not provided in this<br>supplementary dataset. The raw Juno Gravity Science Data may be found at <br>the Planetary Data System:</p> <p> Buccino, D. R. (2016). Juno jupiter gravity science raw data set <br> V1.0, JUNO-J-RSS-1 JUGR-V1.0, NASA planetary data system (PDS). <br> Retrieved from https://atmos.nmsu.edu/PDS/data/jnogrv_1001/<br> </p> <p>=============================================================================<br>ARCHIVE INFORMATION<br>=============================================================================</p> <p> This archive contains two files within the root directory.<br> <br> ROOT<br> `- JunoG34OccData_Egress_v2.csv</p> <p> This data file contains the EGRESS data relevant to the radio<br> occultation. The data is a timeseries of impact parameter, sky<br> sky frequency at X-band and Ka-band, the dual-frequency <br> combination, the calibrated dual-frequency, Total Electron <br> Content.</p> <p> `- JunoG34_GRL_Egress_Profile_v2.csv</p> <p> This data file contains the EGRESS Electron density, and <br> 1-sigma electron density uncertainty.</p> <p> `- JunoG34OccData_Ingress_v2.csv</p> <p> This data file contains the INGRESS data relevant to the radio<br> occultation. The data is a timeseries of impact parameter, sky<br> sky frequency at X-band and Ka-band, the dual-frequency <br> combination, the calibrated dual-frequency, Total Electron <br> Content.</p> <p> `- JunoG34_GRL_Ingress_Profile_v2.csv</p> <p> This data file contains the INGRESS Electron density, and <br> 1-sigma electron density uncertainty.</p> <p>=============================================================================<br>FILE FORMAT<br>=============================================================================</p> <p> This dataset contains only a comma-separated text files which are<br>given with the "*.csv" extension.</p> <p><br> CSV FILES<br> -------------------------------------------------------------------------</p> <p> The Comma-Separated Value (CSV) files are plain-text files. Values in<br> each data file are separated using a comma ",". Each column is defined <br> by a header row which provides a description of each column.<br> </p> <p>=============================================================================<br>ACKNOWLEDGMENTS<br>=============================================================================</p> <p>This work was carried out at the Jet Propulsion Laboratory, <br>California Institute of Technology, under contract with the National <br>Aeronautics and Space Administration. Government sponsorship acknowledged.</p> <p>EG, LGC, PT, MZ and AC are grateful to the Italian Space Agency (ASI) for <br>financial support through Agreement No. 2018-25-HH.0 in the context of ESA's <br>JUICE mission, and Agreement No. 2017-40-H.1-2020, and its extension <br>2017-40-H.02020-13-HH.0, for ESA’s BepiColombo and NASAs Juno radio science <br>experiments. EG is grateful to "Fondazione Cassa dei Risparmi di Forlì" for <br>financial support of his PhD fellowship.</p> <p>PS and AH were supported by NASA Contract NNM06AA75C from the Marshall <br>Space Flight Center under subcontract 699054X from Southwest Research <br>Institute.</p> <p><br>=============================================================================<br>PRIMARY POINT OF CONTACT<br>=============================================================================</p> <p>Dustin Buccino<br>Jet Propulsion Laboratory<br>Planetary Radar and Radio Sciences<br>(818) 393 - 1072<br>Dustin.R.Buccino@jpl.nasa.gov</p> <p>=============================================================================<br>ACRONYMS AND ABBREVIATIONS<br>=============================================================================</p> <p> ASCII American Standard Code for Information Interchange<br> DOY Day of year<br> DSN Deep Space Network<br> JPL Jet Propulsion Laboratory<br> NAIF Navigation Ancillary Information Facility<br> NASA National Aeronautics and Space Administration<br> PDS Planetary Data System<br> RS Radio Science<br> RSS Radio Science Subsystem<br> SIS Software Interface Specification<br> TXT Text file<br> UTC Universal Time, Coordinated</p>
Data affiliated with "Evolution of Flare Activity in GKM Stars Younger than 300 Myr over Five Years of TESS Observations"
<p>Data and Python scripts affiliated with the publication "Evolution of Flare Activity in GKM Stars Younger than 300 Myr over Five Years of TESS Observations" in the American Astronomical Journals. The manuscript pre-print can be found on <a href="https://arxiv.org/abs/2405.00850">arXiv</a>.</p> <p>This repository contains all of the data used to complete the analysis of the aforementioned manuscript, along with the Python scripts used to create all of the figures in the manuscript. Many of the data products from this manuscript are saved as CSVs, with appropriate column names and units, when applicable.</p> <p>Additionally, we include the light curves for all targets in this sample, along with the 'probability light curves,' which were used to identify flares in the TESS data. These data products can be found in the zip file 'TESS_stella_outputs.zip'. The rest of the data product is structured as it is on the <a href="https://github.com/afeinstein20/young-stellar-flares/tree/paper">associated GitHub repository</a>.</p>
Supporting Movies from: Seismo-acoustic observations of crashing ocean waves: Investigating surf monitoring at Coal Oil Point Reserve, Santa Barbara, California
<div> <div> <div> <p>This repository includes supplementary movies from the manuscript titled, "Seismo-acoustic observations of crashing ocean waves: Investigating surf monitoring at Coal Oil Point Reserve, Santa Barbara, California," submitted to the Journal of Geophysical Research: Solid Earth.</p> <p> </p> <p>Movies S1 and S2. These two movies taken during array deployment 4 on October 20, 2023 show the NW tip of Coal Oil Point at the left of the field of view and Sands Beach northwest of that toward the right. Frames have the same figure layout as Figure 4 of the main text.</p> <p>Movie S3. Same as Movies S1 and S2 but with the NW tip of Coal Oil Point at the right of the field of view and Devereux Beach southeast of that toward the left.</p> </div> </div> </div>
Test dataset of VLT/SPHERE/IRDIS H2 observation Injected with simulated disks.
<p>Test data sets used in Juillard et. al. (2023) and , Juillard et. al. (2024), used to compare three different algorithms for processing data sets using ADI alone and to compare the three different strategies: RDI, ADI, and ARDI.</p> <p>This test pipeline consists of a total of 60 test data sets composed of five different disk morphologies, injected at three different contrast levels ($10^{-3}$, $10^{-4}$, and $10^{-5}$), into four different observing ADI sequences of stars without any known circumstellar signal, reflecting different observing conditions. </p> <div><strong><u>CONTENT </u></strong></div> <div> </div> <div>You will find in this folder the battery of test dataset in the compressed folder "test_cubes_sphere.zip". It contains 60 folders, one for each test dataset, with two files in each: "angle.fits" and "cube.fits"</div> <div> </div> <div>Additionaly there folders containg the empty cubes, injected disks, star flux, mask that reprensent the location of the apperture where the flux of the disk was integrated to compute contrast. The Jupyter notebook "asses_quality_of_disk_estimate.ipynb" shows how to compare a disk estimate. We also provided an example disk estimate (file 'X_3_2_0.fits') to try out the notebook.</div> <div> </div> <div>Finally, a folder named "Ref_lib_sphere" containes the different set of references frames library used in the publication Juillard et. al. (2024). In this folder, "ref_lib_X" corresponds to the optimal references for testing using empty cube X, "randref" corresponds to "shuffled" (same for every cube), and "randref_nooverlap_X" corresponds to "excluded." </div> <div>In the “Optimal” case, we used the most correlated frames, which is the same selection used in the first series, where we compare ADI, RDI, and ARDI. In the “Shuffled” case, we randomly selected a sample from the reference libraries dedicated to each of our four ADI test cubessequences into one common reference library. In this test, the random selection contains 25% of frames from the “Optimal” reference library. In the “Excluded” case, we selected for each ADI cube a sample only from references dedicated to the three other ADI cubes, creating a selection that excludes optimal references. The PCC computed for each of the three selections of references is presented in Fig. 5 of Juillard et. al. (2024).</div> <div> </div> <div><span><strong>ABOUT THE DATA</strong></span></div> <p>The data sets, obtained through the High-Contrast Data Center (HCDC), were acquired using the Infrared Dual-Band Imager and Spectrograph (IRDIS, Dohlen et al. 2008; Vigan et al. 2010) camera of the Spectro-Polarimetric High-contrast Exoplanet Research coronagraphic system on the Very Large Telescope (VLT/SPHERE, Beuzit et al. 2019). The test data sets all consist of the $H$2 channel from the dual-band $H$23 set. They were chosen to exhibit a diverse range of characteristics, including low Strehl ratio with a 26\degr\ rotation (ID #1), wind-driven halo (ID #2), an unstable speckle field (ID #3), and good Strehl ratio with an 80\degr\ field rotation (ID #4). The raw data processed with the data handling software (Pavlov et al. 2008) of the HCDC (Delorme et al. 2017), which performs dark, flat, and bad pixel correction on a coronagraphic sequence. <br>For future reference, we computed the mean and standard deviation of the Pearson correlation coefficients (PCC) between each unique pair of frames in the ADI cube. The mean PCC are as follows: Cube #1: $\mu = 0.99$; Cube #2: $\mu = 0.97$; Cube #3: $\mu = 0.93$; Cube #4: $\mu = 0.96$, with standard deviations below $0.001$ for all the cubes.</p> <p><br>The injected disks represent a range of scenarios for both debris and protoplanetary disks. As detailed in Juillard et.al 2023, this selection consists of two 75\degr\ inclined disks with varying sharpness levels (A and B), a 45\degr\ inclined disk with two concentric rings (C), a nearly face-on disk with azimuthal flux variation (D), and a hydrodynamical simulation of a disk with embedded spiral structures and a companion (E). <br>The contrast of the injected disks is determined by measuring the integrated flux within a full width at half-maximum (FWHM)-sized aperture, centered at the peak intensity of the disk, and then dividing this value by the integrated flux within an FWHM-sized aperture of the stellar point spread function. However, we made an exception for the synthetic disk E, where we measured the flux at the companion location.</p> <p>The reference frames were selected from a set of archival IRDIS observations taken with the same filter, coronagraph, and exposure time as the test data sets. These reference targets were observed between 2014 December 11 and 2021 June 1, and the raw data were calibrated through the same process as the test data sets. For each test data set, the PCC was calculated between the frames of the data set and the reference targets, excluding any observations of the data set star taken at different epochs. The PCC was calculated within a circular annulus between 0\farcs31 and 0\farcs67, which captures both the dominant speckle region and position of the waffle pattern, used for precise star centering of a coronagraphic sequence (Zurlo et al. 2014), if it was included in the observation. For each frame in the data set, the 300 best correlated reference frames were identified, and those that appeared in this selection for more than 30\% of the data set frames were selected for the final reference library. </p>
REsolved ALMA and SMA Observations of Nearby Stars (REASONS)
<p>This is the data release of the REASONS survey, a sample of planetesimal belts around nearby stars resolved interferometrically (see journal article for full details). Every tar file corresponds to a planetary system, and contains:<br>Data:<br>1 - the calibrated continuum visibility data in CASA .ms format<br>2 - a FITS file with the non-primary-beam-corrected image of the system. <br>3 - a PDF image of the system<br>Visibility modelling results:<br>4 - an ASCII file ('*_fitresults.txt') containing the results of the MCMC visibility fitting, as reported in Table X in the article but containing extra parameters fitted (such as background sources, extra astrometry for fits of multiple datasets/pointings, weight-rescaling factors)<br>5 - an ASCII notes ('*_fitnotes.txt') file, which should always be consulted when interpreting the fit results, as it typically points out peculiarities in the posterior probability distributions.<br>6 - a PDF of the triangle ('corner') plot of the N-dimensional posterior probability distribution of the fitted parameters, which should be consulted to get a better idea of the results reported in the ASCII files.<br>7 - a PDF image (targetstar_imagecombo.pdf) showing the data, model, residuals and visibility data+model curves, to visually evaluate the goodness of the visibility fit.<br>8 - a PDF image (targetstar.pdf) showing the multiwavelength photometry for the planetary system and a star+belt modified-blackbody fit, with parameters reported in the journal article.<br>Please refer to the journal article for more details on the methods used to obtain these data and modelling results.</p>
Observation of a regular structure formation on the surface of vibrated ball beds started from random lose packing
<p>Near 4,000 2-mm diameter plastic balls were poured 88 times into plexiglass cylinder of internal diameter 26 mm. Then, such initially random loose-packing systems/beds were vibrated vertically with 100 Hz frequency using the vibration table Vibrax (Renfert GmbH, Germany) working in sinusoidal mode until a regular structure was observed on the cylinder surface. The power levels of the vibrations in the recorded ordering of balls were selected to represent all four levels (1, 2, 3 or 4) of vibrations available in the table, where number 1 means the weakest vibration and 4 means the strongest one.</p> <p>Locations of the balls on all sides of a vibrated cylindrical bed were simultaneously recorded on one video frame thanks to the use of two perpendicular mirrors, which enables observation of four images: one of the real cylinder and three of its mirror reflections. View of the table with the attached cylinder containing balls and two mirrors is presented in Fig. 1, while an explanation of the scene, as seen by the recording camera, is given in the scheme in Fig. 2. Video names were given in a standard form explained in the README.txt file.</p>
RW Aur: 1.3mm continuum and CO isotopologues - ALMA observations
<p>The <strong>self-calibrated ALMA observations at 1.3mm wavelength of the RW Aur</strong>, published in <strong>Kurtovic et al., (2024c)</strong>. These observations are separated by epoch, and classified with the sufix LB or SB for "Long Baselines" and "Short Baselines". Please check the <strong>README.txt</strong> for more details about each file.</p>
Collated set of all gravitational wave observations (to current date) from Wikipedia
<p>This is a dataset I needed but couldn't find. So, with the help of Chat GPT (and several hours ot time), I compiled this easy to access html file.</p> <p>It's not perfect but here it is for all of you to enjoy. </p>
TreeGOER: Tree Globally Observed Environmental Ranges
<p><strong>TreeGOER (Tree Globally Observed Environmental Ranges)</strong> is a database that documents the environmental ranges (minimum, maximum, median, mean and 5%, 25%, 75% and 95% quantiles) for 48,129 tree species and for 51 environmental variables, including 38 bioclimatic variables, 8 soil variables and 3 topographic variables. These ranges were calculated after cleaning occurrence records and standardizing species names with the <a href="https://bsapubs.onlinelibrary.wiley.com/doi/10.1002/aps3.11388">WorldFlora</a> R package to <a href="https://onlinelibrary.wiley.com/doi/10.1002/tax.12373">World Flora Online</a> or the <a href="https://www.nature.com/articles/s41597-021-00997-6">World Checklist of Vascular Plants</a> for a global GBIF occurrence download of 44,267,164 occurrences (GBIF.org 2021 <strong>GBIF Occurrence Download</strong> <a href="https://doi.org/10.15468/dl.77gcvq">https://doi.org/10.15468/dl.77gcvq</a>). The 5% and 95% quantiles were calculated separately for two methods of outlier detection and for the full data set. The process of compilation of TreeGOER with 30 arc-seconds global grid layers, two examples of BIOCLIM applications that investigated the effects of climate change on global tree diversity patterns and R scripts to repeat these analyses have been described by Kindt, R. (2023). <strong>TreeGOER: A database with globally observed environmental ranges for 48,129 tree species</strong>. Global Change Biology 29: 6303–6318. <a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914">https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914</a>.</p> <p><strong>TreeGOER </strong>can be used in combination with the <strong>CitiesGOER</strong> database (<a href="https://doi.org/10.5281/zenodo.8175429">https://doi.org/10.5281/zenodo.8175429</a>) that documents the conditions for the same environmental variables (except elevation) for 52,602 cities with a human population ≥ 5000. An alternative to CitiesGOER is the <strong>ClimateForecasts</strong> database (<a href="../records/10776414">https://zenodo.org/records/10776414</a>), a database documenting the environmental conditions at the locations of 15,504 weather stations that was also integrated in the <strong><a href="https://worldagroforestry.org/output/globalusefulnativetrees">GlobalUsefulNativeTrees database</a></strong> (see <a href="https://doi.org/10.1038/s41598-023-39552-1">Kindt et al. 2023</a>). <strong>TreeGOER</strong> could also be used with the <strong>TreeGOER Global Zones</strong> atlas that can be obtained from <a href="https://doi.org/10.5281/zenodo.8252756">https://doi.org/10.5281/zenodo.8252756</a>. This high-resolution atlas includes sheets with global zones for the Climatic Moisture Index (CMI) and the number of months with average temperature > 10 degrees C (Tmo10); these are zones for which presence of the 48,129 species was documented by TreeGOER.</p> <p>Changes between different versions of the databases are documented in a specific sheet in the metadata file.</p> <p><strong>The distribution of the same 48,129 species across historical and contemporary Holdridge Life Zones is available via this Zenodo archive: <a href="https://zenodo.org/records/14020914">https://zenodo.org/records/14020914</a>. The distribution of the same 48,129 species across 1931-1960, 1961-1990 and 1991-2020 Köppen-Geiger climate zones is available via this Zenodo archive: <a href="https://zenodo.org/records/14211619">https://zenodo.org/records/14211619</a>. The distribution of the same 48,129 species for Whittaker Biome Types are available via this Zenodo archive: <a href="https://zenodo.org/records/14908943">https://zenodo.org/records/14908943</a>. Globally observed environmental ranges as in TreeGOER are available since 14<sup>th</sup> June 2024 for another set of species (including several bamboo and hybrid tree species not included in GlobalTreeSearch) via this Zenodo archive: <a href="../records/11652972">https://zenodo.org/records/11652972</a>. <br></strong></p> <p> </p> <p>The development of TreeGOER was supported by the <strong>Darwin Initiative</strong> to project DAREX001 of <em>Developing a Global Biodiversity Standard certification for tree-planting and restoration</em>, by Norway’s <strong>International Climate and Forest Initiative</strong> through the Royal Norwegian Embassy in Ethiopia to the <em>Provision of Adequate Tree Seed Portfolio</em> project in Ethiopia, and by the <strong>Green Climate Fund</strong> through the IUCN-led <em>Transforming the Eastern Province of Rwanda through Adaptation</em> project. When using TreeGOER in your work, cite the publication (Kindt <a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914">2023</a>) as well as this repository using the DOI (<a href="https://doi.org/10.5281/zenodo.7922927">https://doi.org/10.5281/zenodo.7922927</a>).</p> <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.