© 2019 Association for Computing Machinery. Advancements in the field of healthcare information management have led to the development of a plethora of software, medical devices and standards. As a consequence, the rapid growth in quantity and quality of medical data has compounded the problem of heterogeneity; thereby decreasing the effectiveness and increasing the cost of diagnostics, treatment and follow-up. However, this problem can be resolved by using a semi-structured data storage and processing engine, which can extract semantic value from a large volume of patient data, produced by a variety of data sources, at variable rates and conforming to different abstraction levels. Going beyond the traditional relational model and by re-purposing state-of-the-art tools and technologies, we present, the Ubiquitous Health Profile (UHPr), which enables a semantic solution to the data interoperability problem, in the domain of healthcare1