Abstract

Even though computational reproducibility is widely accepted as necessary for research validation and reuse, it is often not considered during the research process. This is because reproducibility tools are typically stand-alone and require additional training to be employed. In this article, we present a solution to foster reproducibility, which is integrated within existing scientific software that is actively used in the LHCb collaboration. Our provenance tracking service captures metadata of a dataset, which is then saved inside the output data file on the disk. The captured information allows a complete understanding of how the file was produced and enables a user to reproduce the dataset, even when the original input code (that was used to initially produce the dataset) is altered or lost. This article describes the implementation of the service and gives examples of its application.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.