Analysis Traceability and Provenance for HEP
Jetendr Shamdasani, Richard McClatchey, Andrew Branson, Zsolt, Kovacs
TL;DR
This paper discusses using CRISTAL to develop provenance-aware analysis tools in neuroscience and proposes its applicability to high-energy physics (HEP) for improved analysis traceability and interoperability.
Contribution
It introduces a generic approach for provenance management using CRISTAL, adaptable from neuroscience to HEP, with a mapping to the PROV model for interoperability.
Findings
CRISTAL-based tools effectively support provenance tracking in neuroscience.
The approach is adaptable to HEP analysis workflows.
Mapping to PROV enables interoperability across domains.
Abstract
This paper presents the use of the CRISTAL software in the N4U project. CRISTAL was used to create a set of provenance aware analysis tools for the Neuroscience domain. This paper advocates that the approach taken in N4U to build the analysis suite is sufficiently generic to be able to be applied to the HEP domain. A mapping to the PROV model for provenance interoperability is also presented and how this can be applied to the HEP domain for the interoperability of HEP analyses.
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