1 dataset found
  1. Z

    SDSS Galaxy Subset

    • data.niaid.nih.gov
    • zenodo.org
    Updated Sep 6, 2022
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    Carvalho, Nuno Ramos (2022). SDSS Galaxy Subset [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_6393487
    Explore at:
    Dataset updated
    Sep 6, 2022
    Dataset authored and provided by
    Carvalho, Nuno Ramos
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The Sloan Digital Sky Survey (SDSS) is a comprehensive survey of the northern sky. This dataset contains a subset of this survey, of 100077 objects classified as galaxies, it includes a CSV file with a collection of information and a set of files for each object, namely JPG image files, FITS and spectra data. This dataset is used to train and explore the astromlp-models collection of deep learning models for galaxies characterisation.

    The dataset includes a CSV data file where each row is an object from the SDSS database, and with the following columns (note that some data may not be available for all objects):

    objid: unique SDSS object identifier

    mjd: MJD of observation

    plate: plate identifier

    tile: tile identifier

    fiberid: fiber identifier

    run: run number

    rerun: rerun number

    camcol: camera column

    field: field number

    ra: right ascension

    dec: declination

    class: spectroscopic class (only objetcs with GALAXY are included)

    subclass: spectroscopic subclass

    modelMag_u: better of DeV/Exp magnitude fit for band u

    modelMag_g: better of DeV/Exp magnitude fit for band g

    modelMag_r: better of DeV/Exp magnitude fit for band r

    modelMag_i: better of DeV/Exp magnitude fit for band i

    modelMag_z: better of DeV/Exp magnitude fit for band z

    redshift: final redshift from SDSS data z

    stellarmass: stellar mass extracted from the eBOSS Firefly catalog

    w1mag: WISE W1 "standard" aperture magnitude

    w2mag: WISE W2 "standard" aperture magnitude

    w3mag: WISE W3 "standard" aperture magnitude

    w4mag: WISE W4 "standard" aperture magnitude

    gz2c_f: Galaxy Zoo 2 classification from Willett et al 2013

    gz2c_s: simplified version of Galaxy Zoo 2 classification (labels set)

    Besides the CSV file a set of directories are included in the dataset, in each directory you'll find a list of files named after the objid column from the CSV file, with the corresponding data, the following directories tree is available:

    sdss-gs/ ├── data.csv ├── fits ├── img ├── spectra └── ssel

    Where, each directory contains:

    img: RGB images from the object in JPEG format, 150x150 pixels, generated using the SkyServer DR16 API

    fits: FITS data subsets around the object across the u, g, r, i, z bands; cut is done using the ImageCutter library

    spectra: full best fit spectra data from SDSS between 4000 and 9000 wavelengths

    ssel: best fit spectra data from SDSS for specific selected intervals of wavelengths discussed by Sánchez Almeida 2010

    Changelog

    v0.0.4 - Increase number of objects to ~100k.

    v0.0.3 - Increase number of objects to ~80k.

    v0.0.2 - Increase number of objects to ~60k.

    v0.0.1 - Initial import.

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Carvalho, Nuno Ramos (2022). SDSS Galaxy Subset [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_6393487

SDSS Galaxy Subset

Explore at:
Dataset updated
Sep 6, 2022
Dataset authored and provided by
Carvalho, Nuno Ramos
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

The Sloan Digital Sky Survey (SDSS) is a comprehensive survey of the northern sky. This dataset contains a subset of this survey, of 100077 objects classified as galaxies, it includes a CSV file with a collection of information and a set of files for each object, namely JPG image files, FITS and spectra data. This dataset is used to train and explore the astromlp-models collection of deep learning models for galaxies characterisation.

The dataset includes a CSV data file where each row is an object from the SDSS database, and with the following columns (note that some data may not be available for all objects):

objid: unique SDSS object identifier

mjd: MJD of observation

plate: plate identifier

tile: tile identifier

fiberid: fiber identifier

run: run number

rerun: rerun number

camcol: camera column

field: field number

ra: right ascension

dec: declination

class: spectroscopic class (only objetcs with GALAXY are included)

subclass: spectroscopic subclass

modelMag_u: better of DeV/Exp magnitude fit for band u

modelMag_g: better of DeV/Exp magnitude fit for band g

modelMag_r: better of DeV/Exp magnitude fit for band r

modelMag_i: better of DeV/Exp magnitude fit for band i

modelMag_z: better of DeV/Exp magnitude fit for band z

redshift: final redshift from SDSS data z

stellarmass: stellar mass extracted from the eBOSS Firefly catalog

w1mag: WISE W1 "standard" aperture magnitude

w2mag: WISE W2 "standard" aperture magnitude

w3mag: WISE W3 "standard" aperture magnitude

w4mag: WISE W4 "standard" aperture magnitude

gz2c_f: Galaxy Zoo 2 classification from Willett et al 2013

gz2c_s: simplified version of Galaxy Zoo 2 classification (labels set)

Besides the CSV file a set of directories are included in the dataset, in each directory you'll find a list of files named after the objid column from the CSV file, with the corresponding data, the following directories tree is available:

sdss-gs/ ├── data.csv ├── fits ├── img ├── spectra └── ssel

Where, each directory contains:

img: RGB images from the object in JPEG format, 150x150 pixels, generated using the SkyServer DR16 API

fits: FITS data subsets around the object across the u, g, r, i, z bands; cut is done using the ImageCutter library

spectra: full best fit spectra data from SDSS between 4000 and 9000 wavelengths

ssel: best fit spectra data from SDSS for specific selected intervals of wavelengths discussed by Sánchez Almeida 2010

Changelog

v0.0.4 - Increase number of objects to ~100k.

v0.0.3 - Increase number of objects to ~80k.

v0.0.2 - Increase number of objects to ~60k.

v0.0.1 - Initial import.

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