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Astronomy began as a visual science, first through careful observations of the sky using either an eyepiece or the naked eye, then on to the preservation of those images with photographic media and finally the digital encoding of that information via CCDs. This last step has enabled astronomy to move into a fully automated era -- where data is recorded, analyzed and interpreted often without any direct visual inspection. Sky in Google Earth completes that circle by providing an intuitive visual interface to some of the largest astronomical imaging surveys covering the full sky. By streaming imagery, catalogs, time domain data, and ancillary information directly to a user, Sky can provide the general public as well as professional and amateur astronomers alike with a wealth of information for use in education and research. We provide here a brief introduction to Sky in Google Earth, focusing on its extensible environment, how it may be integrated into the research process and how it can bring astronomical research to a broader community. With an open interface available on Linux, Mac OS X and Windows, applications developed within Sky are accessible not just within the Google framework but through any visual browser that supports the Keyhole Markup Language. We present Sky as the embodiment of a virtual telescope.
We report the outcomes of a survey that explores the current practices, needs and expectations of the astrophysics community, concerning four research aspects: open science practices, data access and management, data visualization, and data analysis.
We present a high-performance, graphics processing unit (GPU)-based framework for the efficient analysis and visualization of (nearly) terabyte (TB)-sized 3-dimensional images. Using a cluster of 96 GPUs, we demonstrate for a 0.5 TB image: (1) volume
Wide-angle surveys have been an engine for new discoveries throughout the modern history of astronomy, and have been among the most highly cited and scientifically productive observing facilities in recent years. This trend is likely to continue over
Upcoming and future astronomy research facilities will systematically generate terabyte-sized data sets moving astronomy into the Petascale data era. While such facilities will provide astronomers with unprecedented levels of accuracy and coverage, t
We present variability analysis of data from the Northern Sky Variability Survey (NSVS). Using the clustering method which defines variable candidates as outliers from large clusters, we cluster 16,189,040 light curves, having data points at more tha