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145 results for “Gaia”

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zenodo48/100

PM_024651_E_Santa_Perpetua_de_Gaia

<u>File Name</u>: PM_024651_E_Santa_Perpetua_de_Gaia.jpg <br><u>Sublocation</u>: Torre de Pontils <br><u>Location</u>: Santa Perpètua de Gaià <br><u>Province</u>: Catalunya, Tarragona <br><u>Country</u>: Spain <br><u>Header</u>: El lloc; L'església i la torre del castell; <br><u>Description</u>: Torre de Pontils The site The church and the castle tower <br><u>Keywords</u>: Castle, Catalunya, Cultural heritage, Europe, Monuments, Romanesque, Romanesque Catalonia, Ruins, Santa Perpètua de Gaià, Spain, Styles, Tarragona <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>

opencc-by-sa-4.0Nov 2024View details →
zenodo48/100

PM_024674_E_Santa_Perpetua_de_Gaia

<u>File Name</u>: PM_024674_E_Santa_Perpetua_de_Gaia.jpg <br><u>Sublocation</u>: Torre de Pontils <br><u>Location</u>: Santa Perpètua de Gaià <br><u>Province</u>: Catalunya, Tarragona <br><u>Country</u>: Spain <br><u>Header</u>: El lloc; L'església; <br><u>Description</u>: Torre de Pontils The site The church <br><u>Keywords</u>: Castle, Catalunya, Cultural heritage, Europe, Monuments, Romanesque, Romanesque Catalonia, Ruins, Santa Perpètua de Gaià, Spain, Styles, Tarragona <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>

opencc-by-sa-4.0Nov 2024View details →
zenodo48/100

PM_024661_E_Santa_Perpetua_de_Gaia

<u>File Name</u>: PM_024661_E_Santa_Perpetua_de_Gaia.jpg <br><u>Sublocation</u>: Torre de Pontils <br><u>Location</u>: Santa Perpètua de Gaià <br><u>Province</u>: Catalunya, Tarragona <br><u>Country</u>: Spain <br><u>Header</u>: El lloc; La torre del castell; Segle 10; <br><u>Description</u>: Torre de Pontils The site The castle tower 10th century <br><u>Keywords</u>: Castle, Catalunya, Cultural heritage, Europe, Monuments, Romanesque, Romanesque Catalonia, Ruins, Santa Perpètua de Gaià, Spain, Styles, Tarragona <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>

opencc-by-sa-4.0Nov 2024View details →
zenodo48/100

PM_024645_E_Santa_Perpetua_de_Gaia

<u>File Name</u>: PM_024645_E_Santa_Perpetua_de_Gaia.jpg <br><u>Sublocation</u>: Torre de Pontils <br><u>Location</u>: Santa Perpètua de Gaià <br><u>Province</u>: Catalunya, Tarragona <br><u>Country</u>: Spain <br><u>Header</u>: El lloc; <br><u>Description</u>: Torre de Pontils The site <br><u>Keywords</u>: Castle, Catalunya, Cultural heritage, Europe, Monuments, Romanesque, Romanesque Catalonia, Ruins, Santa Perpètua de Gaià, Spain, Styles, Tarragona <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>

opencc-by-sa-4.0Nov 2024View details →
zenodo48/100

PM_024658_E_Santa_Perpetua_de_Gaia

<u>File Name</u>: PM_024658_E_Santa_Perpetua_de_Gaia.jpg <br><u>Sublocation</u>: Torre de Pontils <br><u>Location</u>: Santa Perpètua de Gaià <br><u>Province</u>: Catalunya, Tarragona <br><u>Country</u>: Spain <br><u>Header</u>: El lloc; L'església; <br><u>Description</u>: Torre de Pontils The site The church <br><u>Keywords</u>: Catalunya, Cultural heritage, Europe, Monuments, Romanesque, Romanesque Catalonia, Ruins, Santa Perpètua de Gaià, Spain, Styles, Tarragona <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>

opencc-by-sa-4.0Nov 2024View details →
zenodo48/100

PM_027704_E_Santa_Perpetua_de_Gaia

<u>File Name</u>: PM_027704_E_Santa_Perpetua_de_Gaia.jpg <br><u>Sublocation</u>: Torre de Pontils <br><u>Location</u>: Santa Perpètua de Gaià <br><u>Province</u>: Catalunya, Tarragona <br><u>Country</u>: Spain <br><u>Header</u>: El lloc; L'església; Interior; La nau; Ruïnes; Barroc; <br><u>Description</u>: Torre de Pontils The site The church Interior The nave Ruins Baroque <br><u>Keywords</u>: Baroque, Catalunya, Cultural heritage, Europe, Monuments, Ruins, Santa Perpètua de Gaià, Spain, Styles, Tarragona <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>

opencc-by-sa-4.0Nov 2024View details →
zenodo48/100

PM_027701_E_Santa_Perpetua_de_Gaia

<u>File Name</u>: PM_027701_E_Santa_Perpetua_de_Gaia.jpg <br><u>Sublocation</u>: Torre de Pontils <br><u>Location</u>: Santa Perpètua de Gaià <br><u>Province</u>: Catalunya, Tarragona <br><u>Country</u>: Spain <br><u>Header</u>: El lloc; L'església; Interior; La nau; Ruïnes; Barroc; <br><u>Description</u>: Torre de Pontils The site The church Interior The nave Ruins Baroque <br><u>Keywords</u>: Baroque, Catalunya, Cultural heritage, Europe, Monuments, Ruins, Santa Perpètua de Gaià, Spain, Styles, Tarragona <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>

opencc-by-sa-4.0Nov 2024View details →
zenodo48/100

PM_024667_E_Santa_Perpetua_de_Gaia

<u>File Name</u>: PM_024667_E_Santa_Perpetua_de_Gaia.jpg <br><u>Sublocation</u>: Torre de Pontils <br><u>Location</u>: Santa Perpètua de Gaià <br><u>Province</u>: Catalunya, Tarragona <br><u>Country</u>: Spain <br><u>Header</u>: El lloc; La torre del castell; Segle 10; <br><u>Description</u>: Torre de Pontils The site The castle tower 10th century <br><u>Keywords</u>: Castle, Catalunya, Cultural heritage, Europe, Monuments, Romanesque, Romanesque Catalonia, Ruins, Santa Perpètua de Gaià, Spain, Styles, Tarragona <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>

opencc-by-sa-4.0Nov 2024View details →
zenodo48/100

PM_024662_E_Santa_Perpetua_de_Gaia

<u>File Name</u>: PM_024662_E_Santa_Perpetua_de_Gaia.jpg <br><u>Sublocation</u>: Torre de Pontils <br><u>Location</u>: Santa Perpètua de Gaià <br><u>Province</u>: Catalunya, Tarragona <br><u>Country</u>: Spain <br><u>Header</u>: El lloc; La torre del castell; Segle 10; <br><u>Description</u>: Torre de Pontils The site The castle tower 10th century <br><u>Keywords</u>: Castle, Catalunya, Cultural heritage, Europe, Monuments, Romanesque, Romanesque Catalonia, Ruins, Santa Perpètua de Gaià, Spain, Styles, Tarragona <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>

opencc-by-sa-4.0Nov 2024View details →
zenodo48/100

Gaia Photometric Science Alerts Crossmatch with Gaia DR3 - Feb. 2024

<p>The <a href="http://gsaweb.ast.cam.ac.uk/alerts/home">Gaia Photometric Science Alerts</a> were crossmatched to the Gaia DR3 catalog on <strong>February 23rd, 2024</strong>. We assumed a 1" separation for each crossmatch. The crossmatch was conducted using the <a href="https://lsdb.readthedocs.io/en/latest/">Large Survey Database</a> (LSDB).&nbsp;</p>

opencc-by-4.0Feb 2024View details →
zenodo48/100

An empirical model of the Gaia DR3 selection function

<p>Precomputed maps of the M10 parameter used to predict the completeness of the Gaia DR3 source catalogue.</p> <p><strong>allsky_M10_hpx7.hdf5 </strong>is a tessellation of the whole sky in Galactic nested healpix scheme of order 7.</p> <p><strong>allsky_uniq_10.fits</strong>&nbsp;uses an adaptive resolution and is based on the &#39;uniq&#39; numbering of healpix tiles. Regions of higher density use a finer resolution, up to order 10, chosen so that every tile contains a minimum of twenty sources to compute M10 from.</p> <p>Paper:&nbsp;https://ui.adsabs.harvard.edu/abs/2023A%26A...669A..55C/abstract</p> <p>Tutorial&nbsp;using the GaiaUnlimited python package to query these maps:&nbsp;https://github.com/gaia-unlimited/gaiaunlimited/blob/main/docs/notebooks/dr3-empirical-completeness.ipynb</p> <p>Documentation for the GaiaUnlimited package:&nbsp;https://gaiaunlimited.readthedocs.io/en/latest/</p>

opencc-by-4.0Jun 2023View details →
zenodo44/100

Empirical relationship between calcium triplet equivalent widths and [Fe/H] using Gaia photometry

<p>I present a new empirical relationship for red giant branch stars between the overall metallicity of the star and the sum of equivalent widths of the near-infrared calcium triplet (CaT) spectral lines. This method takes advantage of the all-sky photometry and astrometry of the Gaia&nbsp;mission, and the archival spectra from 2050 red giant branch stars from 18 globular clusters (-0.69&gt;[Fe/H]&gt;-2.44) acquired with the Anglo-Australian Telescope&#39;s AAOmega spectrograph.</p> <ul> <li>&lt;cluster_name&gt;.tar.gz <ul> <li>Raw and reduced spectra for 18 globular clusters (NGC104, NGC6752, NGC6809, NGC288, NGC7099, NGC362, NGC6218, NGC4590, IC4499, NGC1904, ESO452-SC06, ESO280-SC12, NGC1851, NGC6624, NGC2298, Pal 5, NGC5024, Terzan&nbsp;8, NGC5053)</li> <li>Lists of likely members</li> <li>Measured equivalent widths and radial velocities</li> </ul> </li> <li>code.tar.gz <ul> <li>running.py &ndash; calculates the equivalent widths and radial velocities of the stars from the spectra</li> <li>cat_new_params.py &ndash; calculates the best fitting empirical relationship</li> </ul> </li> <li>paper.tar.gz <ul> <li>The LaTeX source for the submitted RNAAS paper.</li> </ul> </li> </ul> <p>&nbsp;</p>

opencc-by-4.0May 2020View details →
zenodo44/100

Catalog of GAIA eDR3 sources within 20 arcsec of pulsars

<p>Catalog of&nbsp;GAIA eDR3 sources within 20 arcsec of pulsars. Details on how the catalog was created can be found in&nbsp;<a href="https://arxiv.org/abs/2011.08075">Antoniadis (2021)</a></p> <p>The source code can be found <a href="https://zenodo.org/record/4378294#.X9-rR-lKjOQ">here</a></p>

opencc-by-4.0Oct 2020View details →
zenodo44/100

UniDAM results with Gaia eDR3 parallaxes

<p>Results of UniDAM run with Gaia eDR3 parallaxes included.</p> <p>+------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | &nbsp; &nbsp; &nbsp; &nbsp; Survey &nbsp; &nbsp; &nbsp; &nbsp; | Input catalogue size | Stars with estimates &nbsp;| &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Reference &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; |<br> | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;| &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;| &nbsp; &nbsp; &nbsp;done using &nbsp; &nbsp; &nbsp; | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; |<br> | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;| &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;| &nbsp;Gaia eDR3 parallaxes | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; |<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | APOGEE (DR16) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;| &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 473307 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;326884 | Ahumada et al. (2020) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; |<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | Bensby &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;714 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 547 | Bensby et al. (2014) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;|<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | Gaia-ESO (DR3) &nbsp; &nbsp; &nbsp; &nbsp; | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;25533 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 20127 | Gilmore et al. (2012) G.Gilmore&amp; S.Randich (2016) |<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | GALAH (DR3) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;| &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 564620 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;505403 | Buder et al. (2020) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; |<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | GCS &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;| &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;13565 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;7633 | Casagrande et al. (2011) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;|<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | LAMOST (DR6) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;5581266 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 4377103 | Luo et al. (2015) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; |<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | LAMOST MRS (DR6) &nbsp; &nbsp; &nbsp; | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 328187 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;223407 | Luo et al. (2015) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; |<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | RAVE (DR6) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 491349 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;347211 | Steinmetz et al. (2020) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; |<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | SEGUE &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;| &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 235595 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;180012 | Yanny et al. (2009) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; |<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+<br> | Total (unique sources) | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;5856273 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 4616931 | &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; |<br> +------------------------+----------------------+-----------------------+---------------------------------------------------+</p>

opencc-by-4.0Dec 2020View details →
zenodo44/100

Gaia EDR3 Catalogs of Machine-Learned Radial Velocities

<p><strong>Gaia EDR3 Catalogs of Machine-Learned Radial Velocities</strong></p> <p>Spatially complete&nbsp;Test-Set and Machine-Learned Radial Velocity (ML-RV)&nbsp;Catalogs described in Dropulic et al., arXiv:<a href="https://arxiv.org/abs/2205.12278">2205.12278</a>. The spatially complete&nbsp;Test-Set Catalog contains a total of 4,332,657&nbsp;stars, while the &nbsp;spatially complete ML-RV Catalog contains 91,840,346 stars. We provide Gaia EDR3 Source IDs, the network-predicted line-of-sight velocity in km/s, and the network-predicted uncertainty in km/s.&nbsp;</p> <p>We have included a simple Jupyter notebook demonstrating how to import the data, and make a simple histogram with it.</p> <p>If you find this catalog useful in your work, please cite Dropulic et al.&nbsp;arXiv:<a href="https://arxiv.org/abs/2205.12278">2205.12278</a>, as well as Dropulic et al. <a href="https://doi.org/10.3847/2041-8213/ac09ef">ApJL 915, L14 (2021)</a>&nbsp;arXiv:<a href="https://arxiv.org/abs/2103.14039">2103.14039</a>.&nbsp;</p>

opencc-by-4.0May 2022View details →
zenodo44/100

Gaia Catalogue of Synthetic Photometry - White Dwarfs (GCSP-WD)

<p>GSPC-WD catalogue&nbsp;</p> <p>This catalogue contains objects described in detail in Gaia Collaboration, Montegriffo et al., 2022, A&amp;A, in press. The description of the catalogue from the paper is given below.</p> <p>We have made the GSPC-WD synthetic photometry available<br> as a stand-alone catalogue27, including SDSS, JKC and JPLUS<br> XPSP and the DA classification probability. The photometry<br> of the individual J-PAS bands, used in the random forest<br> analysis, is not included due to their low signal-to-noise. For<br> WDs classified in SDSS, a subset of which were used in the<br> training/validation of the random forest algorithim, we also include<br> the full SDSS classifications as a separate column in the<br> GSPC-WD catalogue table. When the synthetic spectral bands are very narrow a<br> significant number of sources will have low signal-to-noise. Furthermore,<br> at the edges of the Gaia spectral range, away from<br> the peak of the effective area, this is also true for some stars<br> in the wider bands included in the catalogue. In some extreme<br> cases, there is no significant detection of the object. The random<br> forest algorithm is only able to classify a WD when valid<br> flux measurements are available for every photometric band we<br> include in the analysis. Therefore, no classification is recorded<br> in the catalogue when data for one or more bands is &quot;missing&quot;.<br> In total 15,003 WDs from the total sample of 101,783 are not<br> classified. For completeness, we have made all the flux measurements<br> and corresponding magnitudes available for all objects in<br> the GSPC-WD. Hence magnitude/fluxes with very large errors,<br> up to several times the flux itself, are included. However, where<br> fluxes are negative, the magnitudes are not defined. When using<br> the catalogue, appropriate signal-to-noise cuts are advisable for<br> the specific work in-hand, to ensure data quality.</p> <p>Total number of objects = 101,786; Format 1 object per row, 73 columns of data as listed below.</p> <p>Column &nbsp;Description of contents<br> 1&nbsp;&nbsp; &nbsp;Gaia source_id<br> 2&nbsp;&nbsp; &nbsp;ra<br> 3&nbsp;&nbsp; &nbsp;ra_error<br> 4&nbsp;&nbsp; &nbsp;dec<br> 5&nbsp;&nbsp; &nbsp;dec_error<br> 6&nbsp;&nbsp; &nbsp;JohnsonStd_mag_U<br> 7&nbsp;&nbsp; &nbsp;JohnsonStd_mag_B<br> 8&nbsp;&nbsp; &nbsp;JohnsonStd_mag_V<br> 9&nbsp;&nbsp; &nbsp;JohnsonStd_mag_R<br> 10&nbsp;&nbsp; &nbsp;JohnsonStd_mag_I<br> 11&nbsp;&nbsp; &nbsp;JohnsonStd_flux_U<br> 12&nbsp;&nbsp; &nbsp;JohnsonStd_flux_B<br> 13&nbsp;&nbsp; &nbsp;JohnsonStd_flux_V<br> 14&nbsp;&nbsp; &nbsp;JohnsonStd_flux_R<br> 15&nbsp;&nbsp; &nbsp;JohnsonStd_flux_I<br> 16&nbsp;&nbsp; &nbsp;JohnsonStd_flux_error_U<br> 17&nbsp;&nbsp; &nbsp;JohnsonStd_flux_error_B<br> 18&nbsp;&nbsp; &nbsp;JohnsonStd_flux_error_V<br> 19&nbsp;&nbsp; &nbsp;JohnsonStd_flux_error_R<br> 20&nbsp;&nbsp; &nbsp;JohnsonStd_flux_error_I<br> 21&nbsp;&nbsp; &nbsp;SdssStd_mag_u<br> 22&nbsp;&nbsp; &nbsp;SdssStd_mag_g<br> 23&nbsp;&nbsp; &nbsp;SdssStd_mag_r<br> 24&nbsp;&nbsp; &nbsp;SdssStd_mag_i<br> 25&nbsp;&nbsp; &nbsp;SdssStd_mag_z<br> 26&nbsp;&nbsp; &nbsp;SdssStd_flux_u<br> 27&nbsp;&nbsp; &nbsp;SdssStd_flux_g<br> 28&nbsp;&nbsp; &nbsp;SdssStd_flux_r<br> 29&nbsp;&nbsp; &nbsp;SdssStd_flux_i<br> 30&nbsp;&nbsp; &nbsp;SdssStd_flux_z<br> 31&nbsp;&nbsp; &nbsp;SdssStd_flux_error_u<br> 32&nbsp;&nbsp; &nbsp;SdssStd_flux_error_g<br> 33&nbsp;&nbsp; &nbsp;SdssStd_flux_error_r<br> 34&nbsp;&nbsp; &nbsp;SdssStd_flux_error_i<br> 35&nbsp;&nbsp; &nbsp;SdssStd_flux_error_z<br> 36&nbsp;&nbsp; &nbsp;Jplus_mag_uJAVA<br> 37&nbsp;&nbsp; &nbsp;Jplus_mag_J0378<br> 38&nbsp;&nbsp; &nbsp;Jplus_mag_J0395<br> 39&nbsp;&nbsp; &nbsp;Jplus_mag_J0410<br> 40&nbsp;&nbsp; &nbsp;Jplus_mag_J0430<br> 41&nbsp;&nbsp; &nbsp;Jplus_mag_gJPLUS<br> 42&nbsp;&nbsp; &nbsp;Jplus_mag_J0515<br> 43&nbsp;&nbsp; &nbsp;Jplus_mag_rJPLUS<br> 44&nbsp;&nbsp; &nbsp;Jplus_mag_J0660<br> 45&nbsp;&nbsp; &nbsp;Jplus_mag_iJPLUS<br> 46&nbsp;&nbsp; &nbsp;Jplus_mag_J0861<br> 47&nbsp;&nbsp; &nbsp;Jplus_mag_zJPLUS<br> 48&nbsp;&nbsp; &nbsp;Jplus_flux_uJAVA<br> 49&nbsp;&nbsp; &nbsp;Jplus_flux_J0378<br> 50&nbsp;&nbsp; &nbsp;Jplus_flux_J0395<br> 51&nbsp;&nbsp; &nbsp;Jplus_flux_J0410<br> 52&nbsp;&nbsp; &nbsp;Jplus_flux_J0430<br> 53&nbsp;&nbsp; &nbsp;Jplus_flux_gJPLUS<br> 54&nbsp;&nbsp; &nbsp;Jplus_flux_J0515<br> 55&nbsp;&nbsp; &nbsp;Jplus_flux_rJPLUS<br> 56&nbsp;&nbsp; &nbsp;Jplus_flux_J0660<br> 57&nbsp;&nbsp; &nbsp;Jplus_flux_iJPLUS<br> 58&nbsp;&nbsp; &nbsp;Jplus_flux_J0861<br> 59&nbsp;&nbsp; &nbsp;Jplus_flux_zJPLUS<br> 60&nbsp;&nbsp; &nbsp;Jplus_flux_error_uJAVA<br> 61&nbsp;&nbsp; &nbsp;Jplus_flux_error_J0378<br> 62&nbsp;&nbsp; &nbsp;Jplus_flux_error_J0395<br> 63&nbsp;&nbsp; &nbsp;Jplus_flux_error_J0410<br> 64&nbsp;&nbsp; &nbsp;Jplus_flux_error_J0430<br> 65&nbsp;&nbsp; &nbsp;Jplus_flux_error_gJPLUS<br> 66&nbsp;&nbsp; &nbsp;Jplus_flux_error_J0515<br> 67&nbsp;&nbsp; &nbsp;Jplus_flux_error_rJPLUS<br> 68&nbsp;&nbsp; &nbsp;Jplus_flux_error_J0660<br> 69&nbsp;&nbsp; &nbsp;Jplus_flux_error_iJPLUS<br> 70&nbsp;&nbsp; &nbsp;Jplus_flux_error_J0861<br> 71&nbsp;&nbsp; &nbsp;Jplus_flux_error_zJPLUS<br> 72&nbsp;&nbsp; &nbsp;probability DA<br> 73&nbsp;&nbsp; &nbsp;SDSS WD type</p>

opencc-by-4.0Jun 2022View details →
zenodo44/100

Gaia Data Release 3: Basis function configuration for internally calibrated BP/RP spectra

<p>This XML file contains the basis function configuration adopted for the internally calibrated BP and RP spectra published in Gaia Data Release 3. The same file is included in the GaiaXPy (https://gaia-dpci.github.io/GaiaXPy-website/index.html) python package offering some useful functions to use the spectra.</p> <p>The content of the file and its basic usage are described in detail in Appendix C in the paper &quot;Gaia Data Release 3: Processing and validation of BP/RP low-resolution spectral data&quot;, De Angeli, F. et al. A&amp;A (2022).</p>

opencc-by-4.0Jul 2022View details →
zenodo44/100

Datenaufbereitung zum State-of-the-Art und Fortschritt europäischer Gaia-X sowie Datenraum Initiativen mit einem Schwerpunkt auf Industrie 4.0 Anwendungsfälle

<p><span>In seiner Gesamtheit umfasst der Datensatz eine Sammlung von Initiativen und Projekten, die mit </span><span>Gaia-X sowie Data Spaces im Allgemeinen in Verbindung stehen</span><span>.</span>&nbsp;Ziel der Datensammlung war es, eine detaillierte &Uuml;bersicht &uuml;ber bestehende Projekte zu erhalten und diese systematisch zu kategorisieren, um anschlie&szlig;end spezifische industrielle Anwendungsf&auml;lle herauszuarbeiten und diese zu analysieren. Der Zeitraum dieser Sammlung erstreckte sich von April 2023 bis M&auml;rz 2024. Anzumerken ist, dass s&auml;mtliche zur Verf&uuml;gung stehenden Informationen innerhalb dieses Zeitraums in den Datensatz aufgenommen wurden. Ab M&auml;rz 2024 wurden keine weiteren Daten erfasst, wodurch der Datensatz den aktuellen Stand bis zu diesem Zeitpunkt widerspiegelt.</p> <p>Insgesamt wurden 211 Initiativen aus 281 Quellen zusammengetragen und ausgewertet. Diese unterteilen sich (&uuml;ber alle Dom&auml;nen hinweg) in 102 Data Spaces und 93 Anwendungsf&auml;lle. Die 93 Anwendungsf&auml;lle beinhalten 47 Industrie 4.0 relevante Anwendungsf&auml;lle.</p>

opencc-by-4.0May 2024View details →
zenodo44/100

Various Gaia DR2 subsets

<p>This dataset contains various subsets of DR2 data;</p> <p>- within 20&nbsp;pc<br> - within 25 pc<br> - within 100 pc<br> - within 125 pc<br> - within 200 pc<br> - between 200 and 300 pc<br> - &quot;clean&quot; version of 100 pc (several astrometric quality flag filters applied for cleaner color-mag diagrams)<br> - &quot;clean&quot; version of 200 pc<br> - All&nbsp;white dwarfs within 100 pc<br> - All&nbsp;white dwarfs within 300 pc<br> - All white dwarfs in the Limoges et al. 2015 sample<br> - Rough cut around NGC 6774<br> - Rough cut around M67</p> <p>The file names should be self-explanatory</p>

opencc-by-sa-4.0Jun 2018View details →
zenodo44/100

Exploring the age dependent properties of M and L dwarfs using Gaia and SDSS: The Sample

<p>Sample from &quot;Exploring the age dependent properties of M and L dwarfs using Gaia and SDSS&quot;. We present a sample of 74,216&nbsp;M and L dwarfs constructed from two existing catalogs of cool dwarfs spectroscopically identified in the Sloan Digital Sky Survey (SDSS). We &nbsp;cross-matched the SDSS catalog with Gaia DR2 to obtain parallaxes and proper motions and modified the quality cuts suggested by the Gaia Collaboration to make them suitable for late-M and L dwarfs.&nbsp;</p>

opencc-by-4.0Apr 2019View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record