Data-Intensive Methods in Astronomy

Thomas D. Kitching*, Robert G. Mann, Laura E. Valkonen, Mark Holliman, Alastair Hume, Keith Noddle

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract / Description of output

This chapter first briefly outlines the concept of the virtual observatory as a science response to the growing wealth of astronomical data and the increasing requirement to answer scientific questions using astronomical data from multiple sources. Then, it describes two examples of data-intensive applications from astronomy. The first example centers on running photometric classification algorithms on two existing sky survey databases to generate a catalog of quasars, while the second example outlines the derivation of constraints on cosmological parameters via weak gravitational lensing, which is one of the main science drivers for the next generation of sky surveys. This pair of examples illustrates some of the problems faced by modern astronomy, which require the development of new data-intensive methods and the availability of a computational infrastructure on which to run them.

Original languageEnglish
Title of host publicationThe DATA Bonanza: Improving Knowledge Discovery in Science, Engineering, and Business
PublisherJohn Wiley & Sons Inc.
Number of pages14
ISBN (Print)9781118398647
Publication statusPublished - 9 Apr 2013

Keywords / Materials (for Non-textual outputs)

  • Astronomy
  • Data-intensive methods
  • Gravitational lensing
  • Multiphotometric surveys
  • Quasars
  • Sky survey data
  • Virtual observatory


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