Abstract
In recent years awareness of the importance of preserving the experimental data and scientific software at CERN has been rising. To support this effort, we are presenting a novel approach to structure dependencies of the LHCb data and software to make it more accessible in the long-term future. In this paper, we detail the implementation of a graph database of these dependencies. We list the implications that can be deduced from the graph mining (such as a search for the legacy software), with emphasis on data preservation. Furthermore, we introduce a methodology of recreating the LHCb data, thus supporting reproducible research and data stewardship. Finally, we describe how this information is made available to the users on a web portal that promotes data and analysis preservation and good practise with analysis documentation.
Highlights
The Large Hadron Collider beauty (LHCb) experiment at CERN is a general purpose detector in the forward region, which focuses on investigating the differences between matter and antimatter by studying the decays of beauty (B ) and charm (D) mesons
The major use cases include looking for signals predicted by new theories and improving current measurements, in addition to physics outreach and educational purposes
In this paper we presented the LHCb graph database, a novel approach for recording dependencies between the software and data
Summary
The Large Hadron Collider beauty (LHCb) experiment at CERN is a general purpose detector in the forward region, which focuses on investigating the differences between matter and antimatter by studying the decays of beauty (B ) and charm (D) mesons. The detector has been recording data from proton-proton collisions since 2010 and is expected to record data throughout the 2020s. Due to the rapid development of both the hardware and software used to process the data, many questions have been raised about data compatibility and preservation. We are creating a database to record the metadata of our software and the data provenance. The recorded dependencies are expected to ease the process of running the software and analysing the data in the long-term future. The main objective is to assist analysing HEP data in the future. The major use cases include looking for signals predicted by new theories and improving current measurements, in addition to physics outreach and educational purposes
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