Russian–German Astroparticle Data Life Cycle Initiative

• Published in: Data
• Main 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
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2018
• Subjects: astroparticle physics; cosmic rays; data life cycle management; data curation; meta data; Big Data; deep learning; open data; taiga
• Online Access: https://doi.org/10.3390/data3040056

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.