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A hierarchical approach to Big Data Hierarchical Progressive Surveys (HiPS) and Multi-Order Coverage (MOC) Maps

Abstract : The increasing volumes of astronomical data require practical methods for data access, visualisation and analysis. Hierarchical methods based on sky tessellation techniques enable a multi-resolution approach to astronomy data from the individual pixels up to the whole sky. The Hierarchical Progressive Survey (HiPS) scheme based on the HEALPix is able to describe images, catalogues and 3-dimensional data cubes and is a practical solution for managing large volumes of heterogeneous data. We present the development of HiPS, and its implementation for ~200 diverse data sets at the CDS and other data centres. We highlight the ease of implementation and the use of HiPS with Aladin Lite and other applications.
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https://hal.archives-ouvertes.fr/hal-02994008
Contributor : Mark Allen <>
Submitted on : Saturday, November 7, 2020 - 10:38:44 AM
Last modification on : Thursday, December 3, 2020 - 3:25:44 AM

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Mark G. Allen, Pierre Fernique. A hierarchical approach to Big Data Hierarchical Progressive Surveys (HiPS) and Multi-Order Coverage (MOC) Maps. 2015. ⟨hal-02994008⟩

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