| Issue |
EPJ Web Conf.
Volume 207, 2019
Very Large Volume Neutrino Telescopes (VLVnT-2018)
|
|
|---|---|---|
| Article Number | 08001 | |
| Number of page(s) | 4 | |
| Section | Computing | |
| DOI | https://doi.org/10.1051/epjconf/201920708001 | |
| Published online | 10 May 2019 | |
https://doi.org/10.1051/epjconf/201920708001
Computing in the KM3NeT Research Infrastructure
Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen Centre for Astroparticle Physics (ECAP), Erwin-Rommel-Str. 1, 91058 Erlangen, Germany
* e-mail: jannik.hofestaedt@fau.de
Published online: 10 May 2019
The KM3NeT research infrastructure is currently being established. It will consist of a network of deep-sea neutrino detectors to answer fundamental questions both in particle physics and astrophysics. The complexity and volume of the generated datasets is a challenge for analysis and archival of the data, and requires significant computing resources. The KM3NeT collaboration adopts a tier-like computing model for data management. The KM3NeT data management plan and computing model is presented, and plans for public data with open access are discussed.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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