Schema Evolution publication categorizer

In order to formulate a meaningful XML query, a user must have some knowledge of the schema of the XML documents to be queried. The query will succeed only if the schema of the actual documents is consistent with the user's information. When a user queries a collection of documents collected from heterogeneous XML data sources, there is a high possibility that these documents do not all conform to the same schema assumed by the user, thus causing the query to fail. In this paper, we try to solve this query and data schema mismatching problem by proposing a query translation scheme.

Integration of multiple heterogeneous data sources continues to be a critical problem for many application domains and a challenge for researchers world-wide. With the increasing popularity of the XML model and the proliferation of XML documents on-line, automated matching of XML documents and databases has become a critical problem.

Integration of multiple heterogeneous data sources continues to be a critical problem for many application domains and a challenge for researchers world-wide. One aspect of integration is the translation of schema and data across data model boundaries. Researchers in the past have looked at both customized algorithmic approaches as well as generic meta-modeling approaches as viable solutions. We now take the meta-modeling approach the next step-forward.