Date Added: Mar 2010
Recent advances in high throughput data acquisition technologies in many areas have led to a proliferation of a multitude of physically distributed, autonomous, and often semantically disparate data sources. Effective use of such data in data-driven knowledge acquisition and decision support applications e.g., in health informatics, security informatics, social informatics, etc. presents a data integration challenge. Addressing this data integration challenge requires techniques for bridging the semantic gap between the user and the data sources with respect to both the data schema and the data content.