Name
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 Large Hadron Collider beauty (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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/MCSE.2020.2970625 | Computing in Science & Engineering |
Keywords | DocType | Volume |
data provenance,reproducibility | Journal | 22 |
Issue | ISSN | Citations |
2 | 1521-9615 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ana Trisovic | 1 | 0 | 0.34 |
| Chris R. Jones | 2 | 0 | 0.34 |
| Ben Couturier | 3 | 0 | 0.34 |
| M. Clemencic | 4 | 0 | 0.68 |