An Hierarchical Approach to Big Data

M. G. Allen (1) , P. Fernique (2) , T. Boch (1) , Daniel Durand (3) , A. Oberto (1) , B. Merín (4) , F. Stoehr (5) , F. Genova (1) , F.-X. Pineau (1) , J. Salgado (6)

1 ObAS - Observatoire astronomique de Strasbourg
2 OAS - Observatoire astronomique de Strasbourg
3 CADC - Canadian astronomical data center
4 Herschel Science Center [Madrid]
5 ESO - European Southern Observatory
6 ESA - Agence Spatiale Européenne = European Space Agency

The increasing volumes of astronomical data require practical methods for data exploration, access and visualisation. The Hierarchical Progressive Survey (HiPS) is a HEALPix based scheme that enables a multi-resolution approach to astronomy data from the individual pixels up to the whole sky. We highlight the decisions and approaches that have been taken to make this scheme a practical solution for managing large volumes of heterogeneous data. Early implementors of this system have formed a network of HiPS nodes, with some 250 diverse data sets currently available, with multiple mirror implementations for important data sets. This hierarchical approach can be adapted to expose Big Data in different ways. We describe how the ease of implementation, and local customisation of the Aladin Lite embeddable HiPS visualiser have been keys for promoting collaboration on HiPS.

Domaines: Astrophysique [astro-ph]

M. G. Allen, P. Fernique, T. Boch, Daniel Durand, A. Oberto, et al.. An Hierarchical Approach to Big Data. Astronomical Data Analysis Software and Systems XXV, Oct 2015, Sydney, Australia. ⟨hal-02387849⟩