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Russian–German Astroparticle Data Life Cycle Initiative

Authors :
Igor Bychkov
Andrey Demichev
Julia Dubenskaya
Oleg Fedorov
Andreas Haungs
Andreas Heiss
Donghwa Kang
Yulia Kazarina
Elena Korosteleva
Dmitriy Kostunin
Alexander Kryukov
Andrey Mikhailov
Minh-Duc Nguyen
Stanislav Polyakov
Evgeny Postnikov
Alexey Shigarov
Dmitry Shipilov
Achim Streit
Victoria Tokareva
Doris Wochele
Jürgen Wochele
Dmitry Zhurov
Source :
Data, Vol 3, Iss 4, p 56 (2018)
Publication Year :
2018
Publisher :
MDPI AG, 2018.

Abstract

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.

Details

Language :
English
ISSN :
23065729
Volume :
3
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Data
Publication Type :
Academic Journal
Accession number :
edsdoj.6a7452bfde914384ac2b250ea611144b
Document Type :
article
Full Text :
https://doi.org/10.3390/data3040056