Contingent Models for Integrating Multi-Sourced Heterogeneous Data

In recent years in addition to operational databases, web databases have become an important data source for most of the organization’s. The web databases may be structured, semi-structured or unstructured such as files, HTML pages, etc. and contains several heterogeneity issues. Heterogeneity may be present in different forms, hence the information retrieval from heterogeneous data sources become a tedious task. As the number of sources increases, need more intelligent retrieval techniques. There are number of techniques are available to remove the heterogeneity but the main focus is on information content and semantics of the data. The use of semantic web technologies such as ontology helps to represent such web data into clear information which can be incorporated in a data Warehouse. Ontology also helps to represent the industry requirements in a prescribed way, which needs to be used during the design. This report presents an ontology driven methods which helps to integrate data sources and business requirements from heterogeneous sources. Currently ontologies are being commonly used for dealing semantic knowledge, Information retrieval from distributed heterogeneous data sources. This survey describes different systems and comparisons between them for ontology -based data integration. This paper shows similarities and differences among the systems by comparison and classification.