Title: Generic model of metadata management system for data lakes

Authors: Hamza Elkina; Mohamed Rida Sahib; Taher Zaki

Addresses: Department of Computer Engineering and Intelligent Systems, Laboratory of Innovation in Mathematics and Intelligent Systems, Faculty of Applied Sciences, Ibnou Zohr University, Agadir, Morocco ' Department of Computer Engineering and Intelligent Systems, Laboratory of Innovation in Mathematics and Intelligent Systems, Faculty of Applied Sciences, Ibnou Zohr University, Agadir, Morocco ' Department of Computer Engineering and Intelligent Systems, Laboratory of Innovation in Mathematics and Intelligent Systems, Faculty of Applied Sciences, Ibnou Zohr University, Agadir, Morocco

Abstract: Data lake metadata management is crucial for clearly describing stored data and ensuring efficient search query results, especially for semi-structured and unstructured data. Moreover, high-quality metadata provides the necessary information for decision-making. Therefore, we propose a new approach called Metadata Management for Data Lakes (MMDL) based on metadata quality and classification. Additionally, we introduce a generic model adapted to the context of a data lake by including data lake zones to identify data location during its lifecycle. The model aligns with the proposed approach and enables the handling of metrics used to evaluate metadata quality and metadata sources for provenance classification.

Keywords: metadata; management system; metadata quality; data lake.

DOI: 10.1504/IJMSO.2023.140696

International Journal of Metadata, Semantics and Ontologies, 2023 Vol.16 No.4, pp.315 - 328

Received: 19 Jun 2023
Accepted: 22 Apr 2024
Published online: 30 Aug 2024 *

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