Semantic Harmony: A Framework for Resolving Semantic Heterogeneity Among Data Sources
Abstract: Semantic heterogeneity remains a persistent challenge in data integration efforts, hindering interoperability and knowledge discovery across disparate data sources. In response to this challenge, this research paper presents a novel framework, called Semantic Harmony, designed to address semantic heterogeneity systematically. The framework encompasses semantic mapping, data profiling, normalization, schema integration, semantic mediation, metadata management, and governance practices, providing a holistic approach to achieving semantic coherence among heterogeneous data sources. Through a detailed exploration of each component and practical examples, this paper demonstrates the effectiveness and applicability of the Semantic Harmony framework in facilitating seamless data integration and interoperability.
Keywords: Semantic heterogeneity, Data integration, Semantic mapping, Schema integration, Metadata management, Semantic mediation, Governance
How to Cite?: Sneha Dingre, "Semantic Harmony: A Framework for Resolving Semantic Heterogeneity Among Data Sources", Volume 10 Issue 10, October 2021, International Journal of Science and Research (IJSR), Pages: 1600-1602, https://www.ijsr.net/getabstract.php?paperid=SR24314031402, DOI: https://dx.doi.org/10.21275/SR24314031402