Towards a coherent Data Life Cycle in Astroparticle Physics

The German-Russian Astroparticle Data Life Cycle Initiative (GRADLCI) aims to develop a data life cycle (DLC), namely a clearly defined and maximally automated data processing pipeline for a combined analysis of data from the experiment KASCADE-Grande (Karlsruhe, Germany) and experiments installed at the Tunka Valley in Russia (TAIGA). The important features of such an astroparticle DLC include scalability for handling large amounts of data, heterogeneous data integration, and exploiting parallel and distributed computing at every possible stage of the data processing. In this work we provide an overview of the technical challenges and solutions worked out so far by the GRADLCI group in the framework of a far-reaching analysis and data center. We will touch the peculiarities of data management in astroparticle physics and employing distributed computing for simulations and physics analyses in this field

Tunka-Rex Virtual Observatory

Tunka-Rex (Tunka Radio Extension) was a detector for ultra-high energy cosmic rays measuring radio emission for air showers in the frequency band of 30-80 MHz, operating in 2010s. It provided an experimental proof that sparse radio arrays can be a cost-effective technique to measure the depth of shower maximum with resolutions competitive to optical detectors. After the decommissioning of Tunka-Rex, as last phase of its lifecycle and following the FAIR (Findability — Accessibility — Interoperability — Reuse) principles, we publish the data and software under free licenses in the frame of the TRVO (Tunka-Rex Virtual Observatory), which is hosted at KIT under the partnership with the KCDC and GRADLCI projects. We present the main features of TRVO, its interface and give an overview of projects, which benefit from its open software and data

Development of a data infrastructure for a global data and analysis center in astroparticle physics

Nowadays astroparticle physics faces a rapid data volume increase. Meanwhile, there are still challenges of testing the theoretical models for clarifying the origin of cosmic rays by applying a multi-messenger approach, machine learning and investigation of the phenomena related to the rare statistics in detecting incoming particles. The problems are related to the accurate data mapping and data management as well as to the distributed storage and high-performance data processing. In particular, one could be interested in employing such solutions in study of air-showers induced by ultra-high energy cosmic and gamma rays, testing new hypotheses of hadronic interaction or cross-calibration of different experiments. KASCADE (Karlsruhe, Germany) and TAIGA (Tunka valley, Russia) are experiments in the field of astroparticle physics, aiming at the detection of cosmic-ray air-showers, induced by the primaries in the energy range of about hundreds TeVs to hundreds PeVs. They are located at the same latitude and have an overlap in operation runs. These factors determine the interest in performing a joint analysis of these data. In the German-Russian Astroparticle Data Life Cycle Initiative (GRADLCI), modern technologies of the distributed data management are being employed for establishing a reliable open access to the experimental cosmic-ray physics data collected by KASCADE and the Tunka-133 setup of TAIGA