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A wider adoption of Electronic Health Records (EHR) has produced massive scale clinical data that are stored in distributed and heterogeneous repositories using different formats including structured and unstructured. These data are critically important for an analysis of patient health. However, for an effective analysis, integration of data is sine qua non because it provides a unified view which enables healthcare professionals to extract meaningful information from data collected from various sources. Several standards have been developed to improve data integration and system interoperability. The HL7 messaging is the most successful standard for medical data exchange that facilitates interoperability between health systems. Therefore, converting HL7 messages to RDF enables the data scientists to develop graph-based analytics model. However, unstructured data such as physicians notes, pathology report …