Helmholtz Portfolio Theme Large Scale Data Management And Analysis Lsdma
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Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)
Author: Jung, Christopher
language: en
Publisher: KIT Scientific Publishing
Release Date: 2017-09-20
The Helmholtz Association funded the ""Large-Scale Data Management and Analysis"" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities.
Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)
Author: Christopher [Hrsg]Meyer Jörg [Hr Jung
language: en
Publisher:
Release Date: 2020-10-09
The Helmholtz Association funded the ""Large-Scale Data Management and Analysis"" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
Data-Intensive Radio Astronomy
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 radio telescope 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.