Generating Complex Astronomy Workflows

Astronomy has a rich heritage of discovery using image data sets that cover the full range of the electromagnetic spectrum. Image data sets in one frequency range have often been studied in isolation from those in other frequency ranges. This is mostly a consequence of the diverse properties of the data collections themselves. Images are delivered in different coordinate systems, map projections, spatial samplings, and image sizes, and the pixels themselves are rarely co-registered on the sky. Moreover, the spatial extent of many astronomically important structures, such as clusters of galaxies and star formation regions, is often substantially greater than that of individual images.

Authors and Affiliations

1. Infrared Processing and Analysis Center, California Institute of Technology, Pasadena, CA, 91125, USA

   G. Bruce Berriman, John Good & Anastasia C. Laity

2. Information Sciences Institute, University of Southern California, Marina Del Rey, CA, 90292, USA

   Ewa Deelman, Gurmeet Singh & Mei-Hui Su

3. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA

   Joseph C. Jacob

4. California Institute of Technology, Louisiana State University and Jet Propulsion Laboratory, Baton Rouge, LA, 70803, USA

   Daniel S. Katz

5. Division of Physics, Mathematics, and Astronomy, California Institute of Technology, Pasadena, CA, 91125, USA

   Thomas A. Prince

Editors and Affiliations

1. School of Computer Science, Cardiff University, UK

   Ian J. Taylor PhD

2. The Center for Computation and Technology, Louisiana State University, USA

   Ian J. Taylor PhD

3. Information Sciences Institute, University of Southern California, USA

   Ewa Deelman PhD

4. Department of Computer Science, Indiana University, USA

   Dennis B. Gannon PhD

5. Schools of Computer Science, Physics and Astronomy, Cardiff University, UK

   Matthew Shields PhD

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