From The Front Lines of ADASS 2014 – Visualization

Visualization technology is undergoing a transformation these days, and the October 7 morning session was devoted to advances in visualization. Here I will give a synopsis of some of the talks.

Chris Beaumont described Glue as a “Hackable User Interface,” by which he means interfaces that support not just visualization but the data analysis cycle. Perhaps the best way to get the flavor of his talk is to watch this youTube video of his excellent talk at SciPy2013:

and you can see some more videos on the Glue demo page at http://www.glueviz.org/en/stable/videos.html.

Erik Rosolowsky spoke about the Cube Analysis and Rendering Tool for Astronomy (CARTA), a cube visualization tool under development to meet the needs of the Atacama Large Millimetre/submillimetre Array (ALMA).  When complete, it is intended in the long term as a replacement for the current CASA viewer. Its goal is to navigate and analyze large data cubes by leveraging the capabilities of the CASA viewer (full featured, well developed analytics, and  an expert user-base)  and the CyberSKA viewer (scalable among other things). It can be used as a stand-alone application or as part of an archive architecture. The project uses the PureWeb commercial middleware to allow server side processing, and supports plug-ins from python, yt and glue: plug-ins are a powerful way of extending capabilities and allowing users to customize the visualizer.

Andre Schaaf described how technology intended primarily for gaming can be adapted for use in astronomy, specifically the SDK Oculus Rift.

Pierre Fernique decribed how CDS has been developing and validating new methods to generate, publish and display huge astronomical image data cubes based on the Hierarchical Progressive Survey (HiPS) framework. Their goal is to allow astronomers to interact with massive cube survey data on their desktops with common clients and visualizers, primarily Aladin. Data cubes with two spatial dimensions and an additional spectral or temporal dimension are mapped onto HEALPix grids at different resolutions, and this enables zooming and panning across the sky and in the third dimension.  CDS has  demonstrated the approach on various flavors of cube data, and surveys of cube data, including wide sky coverage data Canadian Galactic Plane Survey, the pointed data cube observations of the CALIFA v500 survey of SDSS galaxies, and composite cubes constructed from multi-band mission imaging, including a 4TB WISE-cube (WISE 3.4, 4.8, 12 and 22 um bands) and a HST-cube built from HST imaging data in 13 bands (F110W, F160W…,F850LP).

I was looking forward to Slava Kitaeff’s talk on “Large astronomy imaging with JPEG2000.” but he was unable to attend. For interested parties, I am including his abstract below:

“The sheer volume of data anticipated to be captured by future radio telescopes, such as, The Square Kilometer Array (SKA) and its precursors present new data challenges, including the cost and technical feasibility of data transport and storage. Servicing such data as images to the end-user in a traditional manner and formats is going to encounter significant performance fallbacks. Thus, image and data compression are going to be important techniques to reduce the data size. We discuss the requirements for extremely large radio spectral-imaging data-cubes, and in this light we analyse the applicability of the approach taken in the JPEG2000 (ISO/IEC 15444) standards. We provide the quantitative analysis of the effects of JPEG2000’s lossy wavelet image compression algorithm on the quality of the radio astronomy imagery data. This analysis is completed by evaluating the completeness, soundness and source parameterisation of the Duchamp source finder using compressed data. We report that the JPEG2000 image compression can be effectively used for noise filtering. “

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This entry was posted in astroinformatics, Astronomy, Computing, Data mining, High performance computing, informatics, information sharing, programming, publishing, Scientific computing, software engineering, software maintenance, visualization and tagged , , , , , , . Bookmark the permalink.

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