| Organizations increasingly need to participate in rapid collaborations with other organizations to be successful and they need to integrate their data sources to share and exchange data in such collaborations. One of the problems that needs to be solved when integrating different data sources is finding semantic correspondences between elements of schemas of disparate data sources (a.k.a. schema matching). Schemas, even those from the same domain, show many semantic heterogeneities. Resolving these heterogeneities is mostly done manually; which is tedious, time consuming, and expensive. Current approaches to automating the process mainly use the schemas and the data as input to discover semantic heterogeneities. However, the schemas and the data are not sufficient sources of semantics. In contrast, we analyze a valuable source of semantics, namely application source code and report design templates, to improve schema matching for information integration. Specifically, we analyze application source code that generate reports to present the data of the organization in a user friendly way. We trace the descriptive information on a report back to the corresponding schema element(s) through reverse engineering of the application source code or report design templates and store the descriptive text, data, and the corresponding schema elements in a report ontology instance. We utilize the information we have discovered for schema matching. Our experiments using a fully functional prototype system show that our approach produces more accurate results than current techniques. |
