| Issue |
EPJ Web Conf.
Volume 245, 2020
24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|
|
|---|---|---|
| Article Number | 06011 | |
| Number of page(s) | 9 | |
| Section | 6 - Physics Analysis | |
| DOI | https://doi.org/10.1051/epjconf/202024506011 | |
| Published online | 16 November 2020 | |
https://doi.org/10.1051/epjconf/202024506011
CERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experiments
European Laboratory for Particle Physics, CERN, Geneva, Switzerland
* e-mail: pamfilos.fokianos@cern.ch
Published online: 16 November 2020
In this paper we present the CERN Analysis Preservation service as a FAIR (Findable, Accessible, Interoperable and Reusable) research data preservation repository platform for LHC experiments. The CERN Analysis Preservation repository allows LHC collaborations to deposit and share the structured information about analyses as well as to capture the individual data assets associated to the analysis. We describe the typical data ingestion pipelines, through which an individual physicist can preserve and share their final n-tuples, ROOT macros, Jupyter notebooks, or even their full analysis workflow code and any intermediate datasets of interest for preservation within the restricted context of experimental collaboration. We discuss the importance of annotating the deposited content with high-level structured information about physics concepts in order to promote information discovery and knowledge sharing inside the collaboration. Finally, we describe techniques used to facilitate the reusability of preserved data assets by capturing and re-executing reproducible recipes and computational workflows using the REANA Reusable Analysis platform.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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