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Astroinformatics (IAU S325)

Astroinformatics (IAU S325)

$125.00 (C)

Part of Proceedings of the International Astronomical Union Symposia and Colloquia

  • Date Published: July 2017
  • availability: In stock
  • format: Hardback
  • isbn: 9781107169951

$ 125.00 (C)
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  • Astronomy has become data-driven in ways that are both quantitatively and qualitatively different from the past: data structures are not simple; procedures to gain astrophysical insights are not obvious; and the informational content of the data sets is so high that archival research and data mining are not merely convenient, but obligatory, as researchers who obtain the data can only extract a small fraction of the science enabled by it. IAU Symposium 325 took place at a crucial stage in the development of the field, when many efforts have carried significant achievements, but the widespread groups have just begun to effectively communicate across specialties, to gather and assimilate their achievements, and to consult cross-disciplinary experts. Bringing together astronomers involved in surveys and large simulation projects, computer scientists, data scientists, and companies, this volume showcases their fruitful exchange of ideas, methods, software, and technical capabilities.

    • Reflects on modern astronomy as data-rich science, which poses both technological and scientific challenges as well as rewards
    • This was the first ever IAU Symposium on astroinformatics, a new discipline, bridging statistics, data mining, astrophysics, ICT, and computer science
    • Collects the contributions of an interdisciplinary team of world experts, to offer the reader the state of the art of the field
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    Product details

    • Date Published: July 2017
    • format: Hardback
    • isbn: 9781107169951
    • length: 420 pages
    • dimensions: 255 x 180 x 20 mm
    • weight: 0.82kg
    • contains: 100 b/w illus.
    • availability: In stock
  • Table of Contents

    1. Astroinformatics projects
    2. Current and future surveys
    3. Data mining and machine learning
    4. Time domain and cosmology
    5. Data visualization
    6. Astroinformatics tools
    7. Archives in astronomy.

  • Editors

    Massimo Brescia, INAF Astronomical Observatory of Capodimonte, Italy

    S. G. Djorgovski, California Institute of Technology

    Eric D. Feigelson, Pennsylvania State University

    Giuseppe Longo, University Federico II, Italy

    Stefano Cavuoti, University Federico II, Italy

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