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Nowadays astroparticle physics faces a rapid data volume increase. Meanwhile,there are still challenges of testing the theoretical models for clarifying theorigin of cosmic rays by applying a multi-messenger approach, machine learningand investigation of the phenomena related to the rare statistics in detectingincoming particles. The problems are related to the accurate data mapping anddata management as well as to the distributed storage and high-performance dataprocessing. In particular, one could be interested in employing such solutionsin study of air-showers induced by ultra-high energy cosmic and gamma rays,testing new hypotheses of hadronic interaction or cross-calibration ofdifferent experiments. KASCADE (Karlsruhe, Germany) and TAIGA (Tunka valley,Russia) are experiments in the field of astroparticle physics, aiming at thedetection of cosmic-ray air-showers, induced by the primaries in the energyrange of about hundreds TeVs to hundreds PeVs. They are located at the samelatitude and have an overlap in operation runs. These factors determine theinterest in performing a joint analysis of these data. In the German-RussianAstroparticle Data Life Cycle Initiative (GRADLCI), modern technologies of thedistributed data management are being employed for establishing a reliable openaccess to the experimental cosmic-ray physics data collected by KASCADE and theTunka-133 setup of TAIGA.

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