Semantic Lifting and Reasoning on the Personalised Activity Big Data Repository for Healthcare Research

The fast growing markets of smart health monitoring devices and mobile applications provide opportunities for common citizens to have capability for understanding and managing their health situations. However, there are many challenges for data engineering and knowledge discovery research to enable efficiently dealing with the data that are collected from heterogonous devices and applications with big volumes and velocity. This paper presents a research work in MyHealthAvatar project, which developed a comprehensive semantic driven knowledge discovery framework based on the integrated data from multiple data resources. The framework applies cloud-based hybrid database architecture of NoSQL and RDF repositories with introductions of semantic oriented data mining and knowledge lifting algorithms. The major aim of the research is to enhance the knowledge management and discovery capabilities and efficiency to support further accurate health risk analysis and lifestyle summarization.