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.
@article{arxiv.0908.0567,
title = {LinkedCT: A Linked Data Space for Clinical Trials},
author = {Oktie Hassanzadeh and Anastasios Kementsietsidis and Lipyeow Lim and Renee J. Miller and Min Wang},
journal= {arXiv preprint arXiv:0908.0567},
year = {2009}
}