Clinical trial data have historically been implemented using relational databases. While this has expedited the dissemination of data among partners, it has hindered on the ability to swiftly query the data by relying on monolithic tables. This paper outlines a project that investigates the semantic enrichment of a large-scale longitudinal clinical trial, the AIBL study, by reusing entities from existing ontologies. The implication of the semantic enrichment of the AIBL study is that it is possible to query the data more effectively and efficiently. We are now able to implement our model and focus on an end-to-end data capture and analysis pipeline to query and visualise clinical trial data. The main contribution of this paper is a discussion of the methodology to semantically enrich clinical trial data using entities from existing ontologies.
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