Using Semantic Web Technologies for Knowledge-Driven Querying of Biomedical Data
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- O’Connor M. et al. (2007) Using Semantic Web Technologies for Knowledge-Driven Querying of Biomedical Data. In: Bellazzi R., Abu-Hanna A., Hunter J. (eds) Artificial Intelligence in Medicine. AIME 2007. Lecture Notes in Computer Science, vol 4594. Springer, Berlin, Heidelberg
Software applications that work with biomedical data have significant knowledge-management requirements. Formal knowledge models and knowledge-based methods can be very useful in meeting these requirements. However, most biomedical data are stored in relational databases, a practice that will continue for the foreseeable future. Using these data in knowledge-driven applications requires approaches that can form a bridge between relational models and knowledge models. Accomplishing this task efficiently is a research challenge. To address this problem, we have developed an end-to-end knowledge-based system based on Semantic Web technologies. It permits formal design-time specification of the data requirements of a system and uses those requirements to drive knowledge-driven queries on operational relational data in a deployed system. We have implemented a dynamic OWL-to-relational mapping method and used SWRL, the Semantic Web Rule Language, as a high-level query language that uses these mappings. We have used these methods to support the development of a participant tracking application for clinical trials and in the development of a test bed for evaluating biosurveillance methods.
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