English

Russian-German Astroparticle Data Life Cycle Initiative

Instrumentation and Methods for Astrophysics 2018-11-30 v1

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.

Keywords

Cite

@article{arxiv.1811.12086,
  title  = {Russian-German Astroparticle Data Life Cycle Initiative},
  author = {Igor Bychkov and Andrey Demichev and Julia Dubenskaya and Oleg Fedorov and Andreas Haungs and Andreas Heiss and Donghwa Kang and Yulia Kazarina and Elena Korosteleva and Dmitriy Kostunin and Alexander Kryukov and Andrey Mikhailov and Minh-Duc Nguyen and Stanislav Polyakov and Evgeny Postnikov and Alexey Shigarov and Dmitry Shipilov and Achim Streit and Victoria Tokareva and Doris Wochele and Jürgen Wochele and Dmitry Zhurov},
  journal= {arXiv preprint arXiv:1811.12086},
  year   = {2018}
}

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Published in Data Journal

R2 v1 2026-06-23T06:24:57.517Z