January 21, 2019 Dataset Open Access

Leike, Reimar H.; Enßlin, Torsten A.

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  <identifier identifierType="DOI">10.5281/zenodo.2543666</identifier>
  <creators>
    <creator>
      <creatorName>Leike, Reimar H.</creatorName>
      <givenName>Reimar H.</givenName>
      <familyName>Leike</familyName>
      <affiliation>Max Planck Institute for Astrophysics, Karl-Schwarzschildstra\ss e 1, 85748 Garching, Germany; Ludwig-Maximilians-Universit\"at, Geschwister-Scholl Platz 1, 80539 Munich, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Enßlin, Torsten A.</creatorName>
      <givenName>Torsten A.</givenName>
      <familyName>Enßlin</familyName>
      <affiliation>Max Planck Institute for Astrophysics, Karl-Schwarzschildstra\ss e 1, 85748 Garching, Germany; Ludwig-Maximilians-Universit\"at, Geschwister-Scholl Platz 1, 80539 Munich, Germany</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Galactic dust absorption maps</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <dates>
    <date dateType="Issued">2019-01-21</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/2543666</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.2542807</relatedIdentifier>
  </relatedIdentifiers>
  <version>1.1</version>
  <rightsList>
    <rights rightsURI="https://opendatacommons.org/licenses/by/1.0/">Open Data Commons Attribution License v1.0</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This dataset contains the 3D structure of interstelllar dust in the vicinity of the Sun, as well as its logarithmic spatial correlation power spectrum. It was computed from Gaia absorption data using Gaussian process regression.&lt;/p&gt;

&lt;p&gt;The small_cube contains only mean and standard deviation while the full_cube contains 50 approximate posterior samples.&lt;/p&gt;</description>
    <description descriptionType="Other">In this version data on the power spectrum was added, the documentation inside the hdf5 files was extended, and all values are now given as float64 instead of float32.</description>
  </descriptions>
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