Research Traceability using Provenance Services for Biomedical Analysis

TL;DR

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

Contribution

It introduces a provenance service architecture tailored for biomedical workflows, adapting CERN's CRISTAL system for effective provenance management in health-related grid computing.

Findings

Provenance service successfully captures workflow data in neuGRID.

System facilitates reconstruction and retrieval of biomedical analysis workflows.

Potential for generalization to broader health grid applications.

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.