E-Health: The Potential of Linked Data and Stream Reasoning for Personalised Healthcare

Stream reasoning over rapidly changing data and its growing applications in real world environments has become a relatively new and challenging area of research in the field of computer science. This research work motivated further investigation into new tools and techniques in stream reasoning for its implementation regarding quick decision making processes, risk analysis, traffic jam, and so on. It has also addressed some significant challenges that needed to be tackled in order to develop a Personalized Health Care System to discover and understand life threatening and life limiting illnesses, such as cancer, Alzheimer's and cystic fibrosis. Reasoning over streaming data has also helped to predict the spread of disease. This paper discusses these ideas further and describes some of the challenges and future work still required within this area. It also provides the basis for our own research and builds on advances made within the Semantic Web to develop a new and novel framework for personalised healthcare.