Russian-German Astroparticle Data Life Cycle Initiative

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.

arXiv commentPublished in Data Journal

References in corpus (24)

• TensorFlow: A system for large-scale machine learning
• Design Concepts for the Cherenkov Telescope Array
• The Pierre Auger Cosmic Ray Observatory
• Observation of a Large-scale Anisotropy in the Arrival Directions of Cosmic Rays above $8\times 10^{18}$ eV
• Science performance of Gaia, ESA's space-astrometry mission
• INTEGRAL/IBIS all-sky survey in hard X-rays
• Measurement of cosmic-ray air showers with the Tunka Radio Extension (Tunka-Rex)
• Extragalactic propagation of ultrahigh energy cosmic-rays
• IceCube - the next generation neutrino telescope at the South Pole
• The Astrophysical Multimessenger Observatory Network (AMON)
• Application of Deep Learning methods to analysis of Imaging Atmospheric Cherenkov Telescopes data
• Deciphering the Dipole Anisotropy of Galactic Cosmic Rays
• Evidence for a connection between the gamma-ray and the highest energy cosmic-ray emissions by BL Lacertae objects
• Search for correlations between the arrival directions of IceCube neutrino events and ultrahigh-energy cosmic rays detected by the Pierre Auger Observatory and the Telescope Array
• The future of gamma-ray astronomy
• The analysis of VERITAS muon images using convolutional neural networks
• The KASCADE Cosmic-ray Data Centre KCDC: Granting Open Access to Astroparticle Physics Research Data
• A Targeted Search for Point Sources of EeV Neutrons
• A correlation between the highest energy cosmic rays and nearby active galactic nuclei detected by Fermi
• Search for a correlation between ANTARES neutrinos and Pierre Auger Observatory UHECRs arrival directions
• Searches for correlation between UHECR events and high-energy gamma-ray Fermi-LAT data
• Towards a Model for Computing in European Astroparticle Physics
• Gamma-Ray Astronomy from the Ground
• Data Provenance: Use Cases for the ESO archive, and Interactions with the Virtual Observatory

Cited by in corpus (5)

• AI for Scientific Discovery is a Social Problem
• Metadata Extraction from Raw Astroparticle Data of TAIGA Experiment
• Interrelation of equivariant Gaussian processes and convolutional neural networks
• AstroDS -- A Distributed Storage for Astrophysics of Cosmic Rays. Current Status
• Distributed data storage for modern astroparticle physics experiments