Designing an Experimental Setup for Data Provenance Tracking using a Public Blockchain: A Case Study using a Water Bottling Plant

Abstract

Data provenance, in an end-to-end supply chain context, refers to the tracking of the origin and history of every raw material, process, packaging and distribution involved in a manufacturing network. The traditional client-server architecture utilised in centralised systems, stores data in a single location, making it vulnerable to single points of failure, data tampering, and unauthorised access. As a result, a lack of data provenance and standardisation for products in a manufacturing supply chain. This leads to a lack of traceability and transparency. There-fore, this article presents a hypothesis that these challenges can be overcome by incorporating data provenance into blockchain-based smart contracts for traceability and transparency. This ar-ticle is structured such that it firstly discusses data provenance traceability with a focus on the cloud-based storage system archi-tecture domains for data provenance traceability across end-to-end supply chains. Secondly, this article sheds more light on the design of an experimental setup for blockchain-based data prove-nance traceability in a manufacturing supply chain using a case study of a water bottling plant. Finally, it showcases and discusses the results of the experiments for this purpose.