We present GEM, an intelligent software assistant for automated data mapping across different datasets or from a dataset to a common data model.  The GEM system automates data mapping by providing precise suggestions for data element mappings.  It further provides an active-learning capability where the process of training the GEM system is optimized.  Our experimental evaluations show that the GEM system provides highly accurate data mappings (over 90% accuracy) for real datasets of thousands of data elements each, in the Alzheimer's disease research domain.  We are currently employing the GEM system to map Alzheimer's disease datasets from around the globe into a common representation, as part of a global Alzheimer's disease integrated data sharing and analysis network called GAAIN.  GEM achieves significantly higher data mapping accuracy for biomedical datasets compared to other state-of-the-art tools for database schema matching that have similar functionality. 
GEM