Visual discovery in large-scale astrophysical datasets: experiences using the Sloan Digital Sky Survey

G. Caniglia, Mel Krokos, U. Becciani, C. Gheller, Bob Nichol, M. Comparato, A. Costa, A. Grillo, Z. Jin, P. Massimino, F. Vitello

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review


Nowadays astronomers are experiencing an unprecedented growth in the quality and quantity of datasets coming from numerical simulations and real-world observations. For example, the increasing availability of high performance computing facilities has given the possibility to perform large-scale simulations of several dimensions. Also, forthcoming astronomical surveys are expected to collect datasets of several petabytes. The emerging need is thus for efficient visual discovery tools for rapid inspection to identify regions of interest in large-scale datasets prior to applying computationally expensive data analysis algorithms. This paper reports our experiences in developing visual discovery tools for the Sloan Digital Sky Survey (SDSS), the most ambitious astronomical survey ever undertaken. We present existing tools and visualization requirements collected from SDSS users for new functionality. We then discuss a range of newly developed visual discovery tools and their applicability to SDSS and finally we conclude with pointers to future developments.
Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference in Visualisation, VIZ ’09
Place of PublicationBarcelona
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Print)9780769537344
Publication statusPublished - 2009


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