NeuroProv - A visualisation system to enhance the utility of provenance Data for neuroimaging analysis

Arshad, Bilal

Abstract

E-Science platforms such as myGRID and NeuGRID for Users are growing at an amazing rate. One of the key barriers to their widespread use in practice is the lack of provenance data to support the reasoning and verification of experimental or analysis results. Clinical researchers use workflows to orchestrate the data present in e-science platforms in order to facilitate processing. Even though most systems capture provenance data and store it, systems rarely make use of it, thus limiting the exploitation of the true potential of such provenance. This thesis investigates mechanisms to visualise provenance data for neuroimaging analysis and to provide means to exploit the true potential of provenance data. In order to achieve this, a visualisation system has been implemented based on the use-cases that have been designed following requirements elicited for neuroimaging analysis. In this research a technique has been used to address the requirements of provenance visualisation for neuroimaging analysis. The prototype system has been tested against the provenance generated by NeuGRID for Users (N4U) as a proof of concept for our research. Different workflows have been visualised to study the efficacy of the proposed solution. Furthermore, evaluation metrics have been defined to determine whether the proposed solution is suitable for the purpose of the research conducted. The results show that the proposed visualisation system enhances the utility of provenance data for neuroimaging analysis and therefore the proposed research can be used to provide value to provenance data for neuroimaging analyses.

• Thesis Type: Thesis
• Publicly Available Date: Jun 5, 2019
• Keywords: visualisation system, NeuroProv, provenance data, neuroimaging
• Public URL: https://uwe-repository.worktribe.com/output/804381
• Additional Information: Additional Information : Supervisors: McClatchey, Richard ([e-mail]); Munir, Kamran ([e-mail]); Shamdasani, Jetendr ([e-mail])
• Award Date: Oct 27, 2015