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Analysis and Knowledge Discovery by Means of Self-Organizing Maps for Gaia Data Releases

  • Marco Antonio Álvarez
  • Carlos Dafonte
  • Daniel Garabato
  • Minia Manteiga
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9950)

Abstract

A billion stars: this is the approximate amount of visible objects estimated to be observed by the Gaia satellite, representing roughly 1 % of the objects in the Galaxy. It constitutes the biggest amount of data gathered to date: by the end of the mission, the data archive will exceed 1 Petabyte. Now, in order to process this data, the Gaia mission conceived the Data Processing and Analysis Consortium, which will apply data mining techniques such as Self-Organizing Maps. This paper shows a useful technique for source clustering, focusing on the development of an advanced visualization tool based on this technique.

Keywords

Gaia mission European Space Agency Data mining Artificial Intelligence Self-Organizing Maps visualizations 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Marco Antonio Álvarez
    • 1
  • Carlos Dafonte
    • 1
  • Daniel Garabato
    • 1
  • Minia Manteiga
    • 2
  1. 1.Department de Tecnologías de la Información y las ComunicacionesUniversidade da Coruña (UDC)A CoruñaSpain
  2. 2.Department de Ciencias de la Navegación y de la TierraUniversidade da Coruña (UDC)A CoruñaSpain

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