Abstract
The increasing capability and sophistication of biomedical instruments has led to rapid generation of large volumes of disparate data that is often characterized as biomedical “big data”. Effective analysis of biomedical big data is providing new insights to advance healthcare research, but it is difficult to efficiently manage big data without a conceptual model, such as ontology, to support storage, query, and analytical functions. In this paper, we describe the Cloudwave platform that uses a domain ontology to support optimal data partitioning, efficient network transfer, visualization, and querying of big data in the neurology disease domain. The domain ontology is used to define a new JSON-based Cloudwave Signal Format (CSF) for neurology signal data. A comparative evaluation of the ontology-based CSF with existing data format demonstrates that it significantly reduces the data access time for query and visualization of large scale signal data.
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