An ontology-based approach for resolving semantic schema conflicts in the extraction and integration of query-based information from heterogeneous web data sources

There are many external resources and heterogeneous data on the internet that an organization or user may need to improve the decision making process. It is therefore, very important and critical that this information are complete, precise and can be acquired on time. Most web sources provide data in semi-structured form on the internet. The combination of semi-structured data from different sources on the internet often fails because of syntactic and semantic differences. The access, retrieval and utilization of information from the different web data sources impose a need for the data to be integrated. Integration of web data is a complex process because of the heterogeneity nature of web data and thus needs some kind of a web data integration system. There are many types of heterogeneity and differences among web sources that makes data integration a difficult process (e.g., different data model, different syntax and semantics in schema and data instance level among web sources). Semantic schema heterogeneity, which refers to the misinterpretation of data at the schema level, is one major obstacle that needs to be overcome in web data integration process. Semantic schema heterogeneity has been identified as one of the most important problems when dealing with interoperability and cooperation among multiple data sources on the internet. In this paper, we recommend a system architecture for web data integration focusing on resolving the problems of semantic schema heterogeneity between web data sources. We propose an ontology-based approach as a solution for the reconciliation of semantic conflicts between web data at the schema level.