  The Linked Clinical Trials (LinkedCT) project aims at publishing the first
open semantic web data source for clinical trials data. The database exposed by
LinkedCT is generated by (1) transforming existing data sources of clinical
trials into RDF, and (2) discovering semantic links between the records in the
trials data and several other data sources. In this paper, we discuss several
challenges involved in these two steps and present the methodology used in
LinkedCT to overcome these challenges. Our approach for semantic link discovery
involves using state-of-the-art approximate string matching techniques combined
with ontology-based semantic matching of the records, all performed in a
declarative and easy-to-use framework. We present an evaluation of the
performance of our proposed techniques in several link discovery scenarios in
LinkedCT.
