Search the repository

A+ | A- | | SLO | ENG

Abstract: In this presentation, the existing open data practices in high energy astro-, particle and astroparticle physics are presented. Open data has become fundamental in astrophysics, particle, and astroparticle physics, enhancing collaboration, reproducibility, and transparency, while accelerating innovation. A recent shift toward openness, marked by data-sharing initiatives and accessible resources, is driving breakthroughs like the multi-messenger observation of GW170817, a neutron star merger detected in both gravitational waves and gamma rays, and the identification of blazar TXS 0506+056 as a high-energy neutrino source. Across these fields, robust efforts are underway to develop and implement FAIR-compliant data policies, with a wide array of supportive tools, standards, protocols, and software already in use (Virtual Observatory in astrophysics, CERN’s Open Data Portal in particle physics, ...). The challenges of astroparticle physics data, often more complex than traditional astrophysics or particle physics data, call for additional coordination and technical advancements to meet FAIR principles effectively. Machine learning also plays a transformative role in these domains, enhancing the analysis of both proprietary and open data to reveal new insights and optimize research methodologies.
Keywords: open data, FAIR data, astrophysics, high-energy particle physics, astroparticle physics, multi-messenger astronomy
Published in RUNG: 06.01.2025; Views: 808; Downloads: 2
Link to file
This document has many files! More...