A Hybrid Semantic Integration Framework for Improving Data Quality - Hamdy, Mahmoud Esmat (2017)
This study aims to develop a new hybrid framework of semantic integration to improve data quality in order to resolve the problem from scattered data sources and rapid expansions of data. The proposed framework is based on a solid background that is inspired by previous studies. Significant and seminal research articles are reviewed based on selection criteria. A critical review is conducted in order to determine a set of qualified semantic technologies that can be used construct a hybrid semantic integration framework. The proposed framework consists of six layers and one component as follows: Source layer, Translation Layer, XML layer, RDF layer, Inference Layer, application layer and ontology component. The proposed framework face two challenges and one conflict, we fix it while compose the framework. The proposed framework examined to improve data quality for four dimensions of data quality dimensions.