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O3.2: Comrie, Angus
Angus Comrie (University of Cape Town)
Adrianna Pinska (University of Cape Town)
Rob Simmonds (University of Cape Town)
Russ Taylor (University of Cape Town)



Time: Mon 09.45 - 10.00
Theme: Astrophysical Data Visualization from Line Plots to Augmented and Virtual Reality
Title: An HDF5 Schema for SKA Scale Image Cube Visualization

In this paper, we describe work that has been performed to create an HDF5 schema to support the efficient visualization of image data cubes that will result from SKA Phase 1 and precursor observations. The schema has been developed in parallel to a prototype client-server visualization system, intended to serve as a testbed for ideas that will be implemented in replacements for the existing CyberSKA and CASA viewers. Most astronomy image files are currently packaged using the FITS standard, however this has a number of shortcomings for very large images. The HDF5 technology suite provides a data model, file format, API, library, and tools, which are are all open and distributed without charge. This enables structured schemas to be created for different applications. We will show how these can be beneficial to packaging radio astronomy (RA) data. In particular, our interest is in supporting fast interactive visualization of data cubes that will be produced by the SKA telescope. Existing HDF5 schemas developed for RA data were unable to meet our requirements. The LOFAR HDF5 schema did not meet performance requirements, due to the approach of storing each 2D image plane in a separate group. The HDFITS schema serves as a starting point for an HDF5 schema that maintains round-trip compatibility with the FITS format, but lacks the additional structures required for pre-calculated and cached datasets. Therefore, we have created a new schema designed to suite our application, though this may be advantageous for other processing and analysis applications. The schema is similar to that of HDFITS, but extensions have been added to support a number of features required for efficient visualization of large data sets. We will discuss these extensions and provide details on performance improvements with commonly used access patterns. We will also describe real-world performance when used with our prototype visualization system.

Link to PDF (may not be available yet): O3-2.pdf