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Russian–German Astroparticle Data Life Cycle Initiative

Matrosov Institute for System Dynamics and Control Theory, Siberian Branch of Russian Academy of Sciences, Lermontov st. 134, P. O. Box 292, 664033 Irkutsk, Russia
Institute Of Mathematics, Economics and Informatics, Irkutsk State University, Gagarin Blvd. 20, Irkutsk 664003, Russia
Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Leninskiye Gory 1(2), 119991 Moscow, Russia
Applied Physics Institute, Irkutsk State University, Gagarin Blvd. 20, 664003 Irkutsk, Russia
Institute for Nuclear Physics, Karlsruhe Institute of Technology, KIT, 76021 Karlsruhe, Germany
Steinbuch Centre for Computing, Karlsruhe Institute of Technology, KIT, 76021 Karlsruhe, Germany
Author to whom correspondence should be addressed.
Received: 12 October 2018 / Revised: 12 November 2018 / Accepted: 24 November 2018 / Published: 28 November 2018
(This article belongs to the Special Issue Data in Astrophysics & Geophysics: Research and Applications)
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Modern large-scale astroparticle setups measure high-energy particles, gamma rays, neutrinos, radio waves, and the recently discovered gravitational waves. Ongoing and future experiments are located worldwide. The data acquired have different formats, storage concepts, and publication policies. Such differences are a crucial point in the era of Big Data and of multi-messenger analysis in astroparticle physics. We propose an open science web platform called ASTROPARTICLE.ONLINE which enables us to publish, store, search, select, and analyze astroparticle data. In the first stage of the project, the following components of a full data life cycle concept are under development: describing, storing, and reusing astroparticle data; software to perform multi-messenger analysis using deep learning; and outreach for students, post-graduate students, and others who are interested in astroparticle physics. Here we describe the concepts of the web platform and the first obtained results, including the meta data structure for astroparticle data, data analysis by using convolution neural networks, description of the binary data, and the outreach platform for those interested in astroparticle physics. The KASCADE-Grande and TAIGA cosmic-ray experiments were chosen as pilot examples. View Full-Text
Keywords: astroparticle physics; cosmic rays; data life cycle management; data curation; meta data; Big Data; deep learning; open data astroparticle physics; cosmic rays; data life cycle management; data curation; meta data; Big Data; deep learning; open data

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Bychkov, I.; Demichev, A.; Dubenskaya, J.; Fedorov, O.; Haungs, A.; Heiss, A.; Kang, D.; Kazarina, Y.; Korosteleva, E.; Kostunin, D.; Kryukov, A.; Mikhailov, A.; Nguyen, M.-D.; Polyakov, S.; Postnikov, E.; Shigarov, A.; Shipilov, D.; Streit, A.; Tokareva, V.; Wochele, D.; Wochele, J.; Zhurov, D. Russian–German Astroparticle Data Life Cycle Initiative. Data 2018, 3, 56.

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