# Russian-German Astroparticle Data Life Cycle Initiative

## TL;DR

This paper introduces ASTROPARTICLE.ONLINE, a web platform designed to unify and analyze diverse astroparticle data from multiple experiments, supporting multi-messenger analysis and outreach in the field.

## Contribution

It presents a comprehensive data life cycle framework and initial results for a platform facilitating data publication, storage, analysis, and outreach in astroparticle physics.

## Key findings

- Development of a metadata structure for astroparticle data
- Implementation of deep learning for multi-messenger analysis
- Pilot testing with KASCADE-Grande and TAIGA experiments

## 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.