Article
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Security and Ownership in User Defined Data Meshes
Version 1
: Received: 4 March 2024 / Approved: 5 March 2024 / Online: 5 March 2024 (15:04:49 CET)
A peer-reviewed article of this Preprint also exists.
Pingos, M.; Christodoulou, P.; Andreou, A.S. Security and Ownership in User-Defined Data Meshes. Algorithms 2024, 17, 169. Pingos, M.; Christodoulou, P.; Andreou, A.S. Security and Ownership in User-Defined Data Meshes. Algorithms 2024, 17, 169.
Abstract
Data Meshes is an approach to data architecture and organization that treats data as a product and focuses on decentralizing data ownership and access. It has recently emerged as a field that presents quite a few challenges related to data ownership, governance, security, monitoring, and observability. To address these challenges, this paper introduces an innovative algorithmic framework leveraging data blueprints to enable the dynamic creation of Data Meshes and Data Products in response to user requests, ensuring that stakeholders will have access to specific portions of the Data Mesh as needed. Ownership and governance concerns are addressed through a unique mechanism involving Blockchain and Non-Fungible Tokens (NFTs). This facilitates secure and transparent transfer of data ownership, with the ability to mint time-based NFTs. By combining these advancements with the fundamental tenets of Data Meshes, this research offers a comprehensive solution to the challenges surrounding data ownership and governance. It empowers stakeholders to navigate the complexities of data management within a decentralized architecture, ensuring a secure, efficient, and user-centric approach to data utilization. The proposed framework is demonstrated using real-world data from a poultry meat production factory.
Keywords
Big Data; Smart Data Processing; Systems of Deep Insight; Data Meshes; Data Lakes; Data Products; Blockchain; NFT; Data Blueprints
Subject
Computer Science and Mathematics, Computer Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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