Research Traceability using Provenance Services for Biomedical Analysis

TL;DR

This paper presents a provenance management system developed within the neuGRID project to capture, store, and reconstruct workflow data in biomedical analyses, enhancing reproducibility and traceability.

Contribution

It introduces a novel provenance service architecture using CRISTAL adapted for biomedical workflows, with potential for broader application in health grid environments.

Findings

Provenance service effectively captures workflow data.

System facilitates reconstruction of analysis workflows.

Adaptation of CRISTAL supports biomedical provenance needs.

Abstract

We outline the approach being developed in the neuGRID project to use provenance management techniques for the purposes of capturing and preserving the provenance data that emerges in the specification and execution of workflows in biomedical analyses. In the neuGRID project a provenance service has been designed and implemented that is intended to capture, store, retrieve and reconstruct the workflow information needed to facilitate users in conducting user analyses. We describe the architecture of the neuGRID provenance service and discuss how the CRISTAL system from CERN is being adapted to address the requirements of the project and then consider how a generalised approach for provenance management could emerge for more generic application to the (Health)Grid community.