Modification of the Algorithm for Dynamic Data Transformation Based on Blockchain Technology for Data Management Systems

Abstract

The rapid growth of data and increasing complexity in various domains necessitate advanced data management solutions that address data quality, security, and interoperability challenges. This paper presents a modified algorithm for dynamic data transformation based on blockchain technology for Master Data Management Systems (MDM), incorporating Ethereum, IPFS and semantic data. Based on the proposed algorithm, an architectural approach is also described that allows developing semantic data management systems. The algorithm assumes data validation, enrichment, and deduplication processes, while also ensuring consistency and trust among multiple participants through the decentralized nature of the blockchain. The semantic data management aspect of the system is achieved using Apache Jena and local ontology, which facilitate semantic interoperability and efficient data processing. The proposed approach addresses the challenge of applying blockchain technology to semantic MDM systems and demonstrates an approach to using the system in Semantic Web, as well as in areas such as finance, healthcare, public administration, and logistics. We evaluated the algorithm using a customer information dataset from an e-commerce platform. The results confirmed the potential of blockchain technology in data management and showed improvements in data accuracy, consistency, completeness, but with some loss in storage efficiency due to the use of blockchain. This paper contributes to developing and evaluating a novel algorithm and architecture, combining blockchain technology, MDM principles, and semantic data management for improving data quality, security, and performance in decentralized systems. However, further research and assessment may be required for the full implementation and evaluation of the system.