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Author | Title | Accn# | Year | Item Type | Claims |
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Vardoulaki, Eleni |
Data-Intensive Radio Astronomy |
I13214 |
2024 |
eBook |
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| Title | Data-Intensive Radio Astronomy : Bringing Astrophysics to the Exabyte Era |
| Author(s) | Vardoulaki, Eleni;Dembska, Marta;Drabent, Alexander;Hoeft, Matthias |
| Publication | Cham, 1. Imprint: Springer
2. Springer Nature Switzerland, 2024. |
| Description | XV, 458 p. 72 illus., 66 illus. in color : online resource |
| Abstract Note | Radio astronomy is irreversibly moving towards the exabyte era. In the advent of all-sky radio observations, efficient tools and methods to manage the large data volume generated have become imperative. This book brings together the knowledge of several different research fields to present an overview of current state-of-the-art methods in data-intensive radio astronomy. Its approach is comprehensive and data-centric, offering a coherent look at the four distinct parts of the data lifecycle: Data creation, storage and archives Data processing Post-processing and data analysis Data access and reuse Large data management has been the topic of discussion within the astronomical community for decades. Some relevant areas explored in this volume are: ongoing technological innovations in interferometers and computing facilities; difficulties and possible solutions for the huge processing demands of radiotelescope projects such as LOFAR, MeerKat, ASKAP; concepts for reliable and fast storage for archiving; and more. Written by experts across astrophysics, high-energy particle physics, data science, and computer science, this volume will help researchers and advanced students better understand the current state of data-intensive radio astronomy and tackle the major problems that may arise from future instruments |
| ISBN,Price | 9783031584688 |
| Keyword(s) | 1. ASTRONOMY
2. Astronomy, Observations and Techniques
3. ASTROPHYSICS
4. COMPUTER SCIENCE
5. Data Analysis and Big Data
6. EBOOK
7. EBOOK - SPRINGER
8. Methodology of Data Collection and Processing
9. Quantitative research
10. Sampling (Statistics)
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| Item Type | eBook |
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