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12 results for “hydrogen map”
The Quest for the Missing Dust: New Herschel Maps of Local Group Galaixes (LMC, SMC, M31, M33) that Restore Previously-Missed Extended Emission, Along With SED-Fitting Results, Hydrogen Gas Maps, and Swift UV Observations
<p>Here we provide the data products from publications:</p> <p>Clark, C.J.R., et al., <em>The Quest for the Missing Dust: I – Restoring Large Scale Emission in Herschel Maps of Local Group Galaxies</em>, ApJ 921 35</p> <p>Clark, C.J.R., et al., <em>The Quest for the Missing Dust: II – Two Orders of Magnitude of Evolution in the Dust-to-Gas Ratio Resolved Within Local Group Galaxies</em>, ApJ 946 42</p> <p>This data concerns four Local Group galaxies: the Large Magellanic Cloud (LMC), the Small Magellanic Cloud (SMC), M31, and M33.</p> <p> </p> <p>For each galaxy, we provide our new Herschel maps, as described in the above publications, which were combined in Fourier space ('feathered') with Planck, IRAS, and COBE data, in order to restore extended emission that was removed from previous Herschel reductions for these galaxies.</p> <p>For each galaxy, we provide this new Herschel data for 5 Hershcel bands: the PACS 100 and 160 <span>\(\mu\)</span>m bands, and the SPIRE 250, 350, and 500 <span>\(\mu\)</span>m bands. This data is provided in FITS format, with one FITS file for each band for each galaxy. Each of these files contains 4 extensions. Extension 1 (IMAGE) provides the standard feathered map. Extension 2 (UNC) provides the uncertainty map. Extension 3 (MASK) provides a binary mask map indicating the portion of the data where reliable, fully-feathered high-resolution coverage is available. Extension 4 provides the foreground-subtracted version of the feathered map (FGND_SUB), the header of which also describes the uncertainty on that subtraction. All maps are in units of MJy/sr (except the MASK extension, which is boolean).</p> <p> </p> <p>We also provide the outputs of our Spectral Energy Distribution (SED) fitting to this data, as described in the publications. For each galaxy, we provide FITS files giving the median value of each parameter in each pixel, and maps of the uncertainties on those medians (being the 68.3% quantile around the median). The parameters are dust mass surface density (SED_Sigma_Mass.fits), dust temperature (SED_Temp.fits), beta 1 (SED_Beta1.fits), beta 2 (SED_Beta2.fits), break wavelength (SED_Break.fits), and 500 <span>\(\mu\)</span>m excess (SED_Excess500.fits). Each of these files contain 2 extensions. Extension 1 (median) provides the map of pixel parameter median values. Extension 2 (uncert) provides the map of uncertainties on those medians.</p> <p>Additionally, we provide the full posterior probability distribution for all SED parameters, consisting of 1000 posterior samples, for all pixels, in the form of a FITS file containing a 4-dimensional hypercube, with axes corresponding to right ascension, declination, parameters (in order: dust mass surface density, dust temperature, beta 1, beta 2, break wavelength, and 500 <span>\(\mu\)</span>m excess), and samples. This is provided as a gzip compressed FITS file for each galaxy.</p> <p>Furthermore, provide the Swift-UVOT maps used in Paper II. This data is provided for Swift-UVOT bands W1, W2, and M2. For each band, we provide a FITS file containing 3 extensions. Extension 1 (SURF_BRI) provides the map of surface brightness in MJy/sr (converted using the Swift-UVOT zero points given in Breeveld et al., 2011). Extension 2 (RATE) provides the map of count rate (in photons/sec). Extension 3 (EXP) provides the map of exposure time (in sec). The maps for the LMC and SMC are those presented in Hagen et al. (2017). The maps for M31 and M33 are were reduced following the same process as those in Hagen et al. (2017), and will be fully presented in Decleir et al. (in prep.), but are provided here for the purposes of reproducibility.</p> <p>Lastly, for each galaxy, we provide our maps of the hydrogen surface density (Sigma_H.fits), and dust-to-gas ratio (DtG.fits). None of the maps presented have had deprojection corrections applied</p> <p> </p>
Wasserstoffatlas (Hydrogen Map) Dataset
<p>This dataset contains the raw data from the Wasserstoffatlas / Hydrogen Map published on <a href="https://wasserstoffatlas.de/">wasserstoffatlas.de</a> as listed here:</p> <table> <tbody> <tr> <td>Description</td> <td>Dataset Name</td> <td>License of Raw Data</td> <td>Source/Additional Information</td> </tr> <tr> <td>Inventory, complete Dataset</td> <td>Bestand.csv</td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td><a href="https://wasserstoffatlas.de/">Methodology Paper Hydrogen Map</a></td> </tr> <tr> <td>Inventory, complete Dataset</td> <td>Bestand.geojson</td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td><a href="https://wasserstoffatlas.de/">Methodology Paper Hydrogen Map</a></td> </tr> <tr> <td>Potential, NUTS 0</td> <td>Potential_nuts0.csv</td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td><a href="https://wasserstoffatlas.de/">Methodology Paper Hydrogen Map</a></td> </tr> <tr> <td>Potential, NUTS 0</td> <td>Potential_nuts0.geojson</td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td><a href="https://wasserstoffatlas.de/">Methodology Paper Hydrogen Map</a></td> </tr> <tr> <td>Potential, NUTS 1</td> <td>Potential_nuts1.csv</td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td><a href="https://wasserstoffatlas.de/">Methodology Paper Hydrogen Map</a></td> </tr> <tr> <td>Potential, NUTS 1</td> <td>Potential_nuts1.geojson</td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td><a href="https://wasserstoffatlas.de/">Methodology Paper Hydrogen Map</a></td> </tr> <tr> <td>Potential, NUTS 2</td> <td>Potential_nuts2.csv</td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td><a href="https://wasserstoffatlas.de/">Methodology Paper Hydrogen Map</a></td> </tr> <tr> <td>Potential, NUTS 2</td> <td>Potential_nuts2.geojson</td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td><a href="https://wasserstoffatlas.de/">Methodology Paper Hydrogen Map</a></td> </tr> <tr> <td>Potential, NUTS 3</td> <td>Potential_nuts3.csv</td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td><a href="https://wasserstoffatlas.de/">Methodology Paper Hydrogen Map</a></td> </tr> <tr> <td>Potential, NUTS 3</td> <td>Potential_nuts3.geojson</td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td><a href="https://wasserstoffatlas.de/">Methodology Paper Hydrogen Map</a></td> </tr> </tbody> </table> <p> </p> <p>The Hydrogen Map relies on multiple data sources, the sources and licenses are as follows (other sources not listed here may be used as well):</p> <table> <tbody> <tr> <td>Description</td> <td>Raw Data</td> <td>License of Raw Data</td> <td>Source/Additional Information</td> </tr> <tr> <td>Solar potentials</td> <td><a href="https://opendata.ffe.de/dataset/vres-generation-potentials-europe-nuts-3/">vRES Generation Potentials (Europe NUTS-3)</a></td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td>München: Forschungsstelle für Energiewirtschaft e. V. (FfE), 2020.</td> </tr> <tr> <td>Electricity demand of Tertiary Sector</td> <td><a href="https://opendata.ffe.de/dataset/load-curves-of-the-tertiary-sector-extremos-solideu-scenario-europe-nuts-3/">Load Curves of the Tertiary Sector – eXtremOS solidEU Scenario (Europe NUTS-3)</a></td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td>München: Forschungsstelle für Energiewirtschaft e. V. (FfE), 2021.</td> </tr> <tr> <td>Electricity demand of Transport Sector</td> <td><a href="https://opendata.ffe.de/dataset/load-curves-of-the-transport-sector-extremos-solideu-scenario-europe-nuts-3/">Load Curves of the Transport Sector – eXtremOS solidEU Scenario (Europe NUTS-3)</a></td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td>München: Forschungsstelle für Energiewirtschaft e. V. (FfE), 2021.</td> </tr> <tr> <td>Electricity demand of Private Household Sector</td> <td><a href="https://opendata.ffe.de/dataset/load-curves-of-the-private-household-sector-extremos-solideu-scenario-europe-nuts-3/">Load Curves of the Private Household Sector – eXtremOS solidEU Scenario (Europe NUTS-3)</a></td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td>München: Forschungsstelle für Energiewirtschaft e. V. (FfE), 2021.</td> </tr> <tr> <td>Electricity demand of Industry Sector</td> <td><a href="https://opendata.ffe.de/dataset/load-curves-of-the-industry-sector-extremos-solideu-scenario-europe-nuts-3/">Load Curves of the Industry Sector – eXtremOS solidEU Scenario (Europe NUTS-3)</a></td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td>München: Forschungsstelle für Energiewirtschaft e. V. (FfE), 2021.</td> </tr> <tr> <td>Hydrogen refuelling stations</td> <td><a href="https://h2-map.eu/">European Hydrogen Refuelling Station Availability System (E-HRS-AS)</a></td> <td><a href="https://joinup.ec.europa.eu/collection/eupl/eupl-text-eupl-12">EUPL-1.2</a></td> <td>© Clean Hydrogen JU, 2020</td> </tr> <tr> <td>Atlite</td> <td><a href="https://pypi.org/project/atlite/">Atlite</a></td> <td>data: <a href="https://creativecommons.org/publicdomain/zero/1.0/legalcode">CC0-1.0</a> & docs:<a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td>© 2016-2021 The Atlite Authors.</td> </tr> <tr> <td>PyPSA</td> <td><a href="https://pypi.org/project/pypsa/">PyPSA</a></td> <td>(<a href="https://github.com/PyPSA/PyPSA/blob/master/LICENSE.txt">MIT Licence</a></td> <td>© 2015-2022 PyPSA Developers</td> </tr> <tr> <td>Agora hydrogen demand</td> <td><a href="https://www.agora-energiewende.de/en/publications/no-regret-hydrogen">No regret hydrogen study</a></td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td>Agora Energiewende and AFRY Management Consulting (2021): No-regret hydrogen: Charting early steps for H₂ infrastructure in Europe.</td> </tr> <tr> <td>Bioethanolanlagen</td> <td><a href="https://www.bdbe.de/biokraftstoff-bioethanol/zellulose-ethanol">Bioethanolwerke</a></td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td>BDBe - Bundesverband der deutschen Bioethanolwirtschaft e.V.</td> </tr> <tr> <td>Biomethanaufbereitung</td> <td><a href="https://www.biogaspartner.de/einspeiseatlas/">Biomethanaufbereitungsanlagen</a></td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td>Deutsche Energie-Agentur </td></tr> <tr> <td>PRTR Germany</td> <td><a href="https://thru.de/daten/">Thru.de des Umweltbundesamtes</a></td> <td><a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC-BY-4.0</a></td> <td>Thru.de des Umweltbundesamtes</td> </tr> <tr> <td>Raumordnungsplan BSH</td> <td><a href="https://www.geoseaportal.de/atomfeeds/Raumordnungsplan_AWZ_de.xml#download=1">GeoSeaPortal des BSH</a></td> <td><a href="http://www.govdata.de/dl-de/by-2-0">dl-de/by-2-0</a></td> <td>Bundesamt für Seeschifffahrt und Hydrographie (BSH) Download Raumordnungsplan AWZ (Veröffentlichung: 01.09.2021, letzte Änderung: 23.11.2021)</td> </tr> <tr> <td>Markstammdatenregister</td> <td><a href="https://www.marktstammdatenregister.de/MaStR/Datendownload">Marktstammdatenregister</a></td> <td><a href="http://www.govdata.de/dl-de/by-2-0">dl-de/by-2-0</a></td> <td>© 2022 Bundesnetzagentur für Elektrizität, Gas, Telekommunikation, Post und Eisenbahnen; Pressestelle</td> </tr> <tr> <td>Akteursatlas</td> <td> </td> <td> </td> <td> <p><a href="https://www.wasserstoff-kompass.de/">Wasserstoff-Kompass</a></p> </td> </tr> <tr> <td>OpenStreetMap</td> <td><a href="https://download.geofabrik.de/">Geofabrik</a></td> <td><a href="https://opendatacommons.org/licenses/odbl/1-0/">ODbL v1.0</a></td> <td>© 2023 OpenStreetMap</td> </tr> <tr> <td>Digitales Landbedeckungsmodell für Deutschland, Stand 2018</td> <td><a href="https://gdz.bkg.bund.de/index.php/default/digitale-geodaten/digitale-landschaftsmodelle/digitales-landbedeckungsmodell-fur-deutschland-stand-2018-lbm-de2018.html">lbm-de2018-003</a></td> <td><a href="https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/mnt/c/Users/bif38590/Documents/Git/htwo-map/www.govdata.de/dl-de/by-2-0">dl-de/by-2-0</a></td> <td>© GeoBasis-DE / BKG 2023</td> </tr> <tr> <td>Copernicus Slope</td> <td><a href="https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1-0-and-derived-products">EU-DEM v1.1</a></td> <td><a href="https://opendatacommons.org/licenses/odbl/1-0/">ODbL v1.0</a></td> <td>© 2023 Copernicus</td> </tr> <tr> <td>FFH-Gebiete Deutschland</td> <td><a href="https://www.geoportal.de/Metadata/7930E9E6-2C9A-4A0B-8D48-99FA81E74086">Metadaten</a></td> <td><a href="https://sg.geodatenzentrum.de/web_public/gdz/lizenz/geonutzv.pdf">GeoNutzV</a></td> <td>© 2023 Bundesamt für Naturschutz (BfN)</td> </tr> <tr> <td>Landschaftsschutzgebiete Deutschland</td> <td><a href="https://www.geoportal.de/Metadata/8dceff1a-7bc1-4a49-9c08-a3f6b37f1b2b">Metadaten</a></td> <td><a href="https://sg.geodatenzentrum.de/web_public/gdz/lizenz/geonutzv.pdf">GeoNutzV</a></td> <td>© 2023 Bundesamt für Naturschutz (BfN)</td> </tr> <tr> <td>Ramsar-Gebiete Deutschland</td> <td><a href="https://www.geoportal.de/Metadata/9142A292-84C1-4859-A07F-39CD6185D076">Metadaten</a></td> <td><a href="https://sg.geodatenzentrum.de/web_public/gdz/lizenz/geonutzv.pdf">GeoNutzV</a></td> <td>© 2023 Bundesamt für Naturschutz (BfN)</td> </tr> <tr> <td>Landschaftsschutzgebiete Nordrhein-Westfalen</td> <td><a href="https://www.geoportal.de/Metadata/ef9d0151-7746-44d6-9930-36482ea550cd">Metadaten</a></td> <td><a href="https://www.govdata.de/dl-de/zero-2-0">Datenlizenz Deutschland – Zero – Version 2.0</a></td> <td>© 2023 Landesamt für Natur, Umwelt und Verbraucherschutz Nordrhein-Westfalen</td> </tr> <tr> <td>Vogelschutzgebiete Deutschland</td> <td><a href="https://www.geoportal.de/Metadata/3F448817-6212-4AF0-B498-DB8981490571">Metadaten</a></td> <td><a href="https://sg.geodatenzentrum.de/web_public/gdz/lizenz/geonutzv.pdf">GeoNutzV</a></td> <td>© 2023 Bundesamt für Naturschutz (BfN)</td> </tr> </tbody> </table> <p>Funded by BMBF Germany (FKZ.: 03EW0013A).</p>
Weather Data Cutouts for the Wasserstoffatlas (Hydrogen Map)
<p>The cutouts are required to calculate the solar PV and wind onshore feed-in profiles of the <a href="http://wasserstoffatlas.de">Wasserstoffatlas</a>.</p> <p>The provided <strong>cutouts </strong>are spatiotemporal subsets of the European weather data from the <a href="https://software.ecmwf.int/wiki/display/CKB/ERA5+data+documentation">ECMWF ERA5</a> reanalysis dataset and the <a href="https://wui.cmsaf.eu/safira/action/viewDoiDetails?acronym=SARAH_V002">CMSAF SARAH-2</a> solar surface radiation dataset for the year 2013. They have been prepared by and are for use with the <a href="https://github.com/PyPSA/atlite">atlite</a> tool (<a href="https://atlite.readthedocs.io/">https://atlite.readthedocs.io/</a>).</p> <p><strong>ECMWF ERA5</strong></p> <ul> <li><strong>Source: </strong><a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview</a></li> <li><strong>Terms of Use: </strong><a href="https://cds.climate.copernicus.eu/api/v2/terms/static/20180314_Copernicus_License_V1.1.pdf">https://cds.climate.copernicus.eu/api/v2/terms/static/20180314_Copernicus_License_V1.1.pdf</a></li> </ul> <p><strong>CMSAF SARAH-2</strong></p> <ul> <li>Pfeifroth, Uwe; Kothe, Steffen; Müller, Richard; Trentmann, Jörg; Hollmann, Rainer; Fuchs, Petra; Werscheck, Martin (2017): Surface Radiation Data Set - Heliosat (SARAH) - Edition 2, Satellite Application Facility on Climate Monitoring, DOI:10.5676/EUM_SAF_CM/SARAH/V002, <a href="https://doi.org/10.5676/EUM_SAF_CM/SARAH/V002">https://doi.org/10.5676/EUM_SAF_CM/SARAH/V002</a>.</li> <li><strong>Terms of Use:</strong> <a href="https://www.eumetsat.int/cs/idcplg?IdcService=GET_FILE&dDocName=pdf_leg_data_policy&allowInterrupt=1&noSaveAs=1&RevisionSelectionMethod=LatestReleased">https://www.eumetsat.int/cs/idcplg?IdcService=GET_FILE&dDocName=pdf_leg_data_policy&allowInterrupt=1&noSaveAs=1&RevisionSelectionMethod=LatestReleased</a></li> </ul>
Supplementary material: How much hydrogen could we need in New Zealand? Understanding the diverse hydrogen applications and their regional mapping
<p>Dataset on the future hydrogen demand for New Zealand, mapped to its 16 regions. Supplementary material of the publication: "How much hydrogen could we need in New Zealand? Understanding the diverse hydrogen applications and their regional mapping"</p>
Wasserstoffatlas Deutschland (Hydrogen Map) Dataset
<p>Input files required for Hydrogen Map workflow in the project "Wasserstoffatlas Deutschland", funded by the BMBF.</p>
Mapping of hydrogen sulfide molecular targets in human keratinocytes
GEO Series GSE148985. Homo sapiens. 10 samples. Type: Expression profiling by high throughput sequencing.
DAWN GRAND MAP CERES HYDROGEN MAP V1.0
A global map of the concentration of hydrogen within the regolith of asteroid 1 Ceres on twenty-degree quasi-equal-area pixels is provided. Hydrogen concentrations were determined from thermal+epithermal neutron counting data acquired by the NASA Dawn mission's Gamma Ray and Neutron Detector (GRaND) while in low altitude mapping orbit, about 385 km from Ceres' surface (about 0.8 body radii altitude). The concentrations are representative of Ceres's bulk regolith to depths up to a few decimeters with a spatial resolution of about 600-km full-width-at-half-maximum of arc length on the surface. The methods used to determine hydrogen concentration are described by PRETTYMANETAL2017.
DAWN GRAND MAP VESTA HYDROGEN ABUNDANCE V1.0
A global map of the abundance of hydrogen in micrograms/g within the regolith of asteroid 4 Vesta is provided for two-degree equal-angle pixels. Hydrogen abundances were determined from epithermal neutron counting data acquired by the NASA Dawn mission's Gamma Ray and Neutron Detector (GRaND) while in low altitude mapping orbit, about 210 km from Vesta's surface. The abundances are representative of Vesta's bulk regolith composition to depths of a few decimeters with a spatial resolution of about 300-km full-width-at-half-maximum of arc length on the surface. The methods used to determine hydrogen abunance are described by PRETTYMANETAL2012.
DAWN GRAND MAP CERES SMOOTHED HYDROGEN MAP V1.0
A smoothed, global map of the concentration of hydrogen within the regolith of asteroid 1 Ceres on two-degree equal-angle pixels is provided. Hydrogen concentrations were determined from thermal+epithermal neutron counting data acquired by the NASA Dawn mission's Gamma Ray and Neutron Detector (GRaND) while in low altitude mapping orbit, about 385 km from Ceres' surface (about 0.8 body radii altitude). The concentrations are representative of Ceres's bulk regolith to depths up to a few decimeters with a spatial resolution of about 600-km full-width-at-half-maximum of arc length on the surface. The methods used to determine hydrogen concentration are described by PRETTYMANETAL2017.
DAWN GRAND MAP CERES HYDROGEN MAP V1.0
A global map of the concentration of hydrogen within the regolith of asteroid 1 Ceres on twenty-degree quasi-equal-area pixels is provided. Hydrogen concentrations were determined from thermal+epithermal neutron counting data acquired by the NASA Dawn mission's Gamma Ray and Neutron Detector (GRaND) while in low altitude mapping orbit, about 385 km from Ceres' surface (about 0.8 body radii altitude). The concentrations are representative of Ceres's bulk regolith to depths up to a few decimeters with a spatial resolution of about 600-km full-width-at-half-maximum of arc length on the surface. The methods used to determine hydrogen concentration are described by PRETTYMANETAL2017.
DAWN GRAND MAP VESTA HYDROGEN ABUNDANCE V1.0
A global map of the abundance of hydrogen in micrograms/g within the regolith of asteroid 4 Vesta is provided for two-degree equal-angle pixels. Hydrogen abundances were determined from epithermal neutron counting data acquired by the NASA Dawn mission's Gamma Ray and Neutron Detector (GRaND) while in low altitude mapping orbit, about 210 km from Vesta's surface. The abundances are representative of Vesta's bulk regolith composition to depths of a few decimeters with a spatial resolution of about 300-km full-width-at-half-maximum of arc length on the surface. The methods used to determine hydrogen abunance are described by PRETTYMANETAL2012.
DAWN GRAND MAP CERES SMOOTHED HYDROGEN MAP V1.0
A smoothed, global map of the concentration of hydrogen within the regolith of asteroid 1 Ceres on two-degree equal-angle pixels is provided. Hydrogen concentrations were determined from thermal+epithermal neutron counting data acquired by the NASA Dawn mission's Gamma Ray and Neutron Detector (GRaND) while in low altitude mapping orbit, about 385 km from Ceres' surface (about 0.8 body radii altitude). The concentrations are representative of Ceres's bulk regolith to depths up to a few decimeters with a spatial resolution of about 600-km full-width-at-half-maximum of arc length on the surface. The methods used to determine hydrogen concentration are described by PRETTYMANETAL2017.
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.