Visualizing Provenance In A Supply chain Using Ethereum Blockchain
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Visualization is a widely used in different fields of studies such as supply chain management when there is a need to communicate information to general users. However, there are multiple limitations and problems with visualizing information within traditional systems. In traditional systems, data is in control of one single authority; so data is mutable and there is no guarantee that system administer does not change the data to achieve a desired result. Besides, such systems are not transparent and users do not have any access to the data flow. In this thesis, the main goal was to visualize information that has been saved on top of a new technology named blockchain to overcome the aforementioned problems. All the records in the system are saved on the blockchain and data is pulled out from blockchain to be used in visualization. To have a better insight, a review has been done on relevant studies about blockchain, supply chain and visualization. After identifying the gap in literature review, an architecture was proposed that was used in the implementation. The implementation contains, a system on top of ethereum blockchain and front-end which allows users to interact with the system. In the system, all the information about products and all the transactions that ever happened in the system, are recorded on the blockchain. Then, data was retrieved from the blockchain and used to visualize provenance of products on Google Map API. After implementing the system, the performance was evaluated to make sure that it can handle different situations where various number of clients sending request to the system simultaneously. The performance was as expected in which system responds longer when number of clients sending requests were growing. The proposed solution fill the gap that was identified in the literature review. By adding provenance visualization users can explore previous owners and locations of a product in a trustable manner. Future research can focus on analysis of data which will allow organizations to make informed decisions on choosing popular products to sell.
DegreeMaster of Science (M.Sc.)
CommitteeVassileva, Julita; Roy, Chanchal; Zhang, Chris
Copyright DateSeptember 2019
Blockchain, Supply Chain, Provenance