A case study on the use of workflow technologies for scientific analysis: Gravitational wave data analysis

Duncan A. Brown, Patrick R. Brady, Alexander Dietz, Junwei Cao, Ben Johnson, John McNabb

Research output: Chapter in Book/Entry/PoemChapter

89 Scopus citations


Modern scientific experiments acquire large amounts of data that must be analyzed in subtle and complicated ways to extract the best results. The Laser Interferometer Gravitational Wave Observatory (LIGO) is an ambitious effort to detect gravitational waves produced by violent events in the universe, such as the collision of two black holes or the explosion of supernovae [37,258]. The experiment records approximately 1 TB of data per day, which is analyzed by scientists in a collaboration that spans four continents. LIGO and distributed computing have grown up side by side over the past decade, and the analysis strategies adopted by LIGO scientists have been strongly influenced by the increasing power of tools to manage distributed computing resources and the workflows to run on them. In this chapter, we use LIGO as an application case study in workflow design and implementation. The software architecture outlined here has been used with great efficacy to analyze LIGO data [2-5] using dedicated computing facilities operated by the LIGO Scientific Collaboration, the LIGO Data Grid. It is just the first step, however. Workflow design and implementation lies at the interface between computing and traditional scientific activities. In the conclusion, we outline a few directions for future development and provide some long-term vision for applications related to gravitational wave data analysis.

Original languageEnglish (US)
Title of host publicationWorkflows for e-Science
Subtitle of host publicationScientific Workflows for Grids
PublisherSpringer London
Number of pages21
ISBN (Print)9781846285196
StatePublished - 2007
Externally publishedYes


  • Data access
  • Gravitational wave data analysis
  • Grid computing
  • Signal processing

ASJC Scopus subject areas

  • General Computer Science


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