ABSTRACT
Medical healthcare and epidemic outbreak data are heavily interconnected and unstructured type of dataset. It is very difficult to represent and manage the large number of relationships between data items using traditional database management systems. Therefore, it is required to find a new framework to handle these datasets. A knowledge graph is a data analytics tool which can be used to handle a connection-rich type of dataset. It is an arrangement of entities (real-world objects or concepts) in the form of a network where these entities are linked to each other; therefore, knowledge graph is an efficient choice for the representation and analysis of linked data. This chapter provides the benefits that can be derived from a graph-based approach for analyzing dynamic, heterogeneous, and unstructured data applications in epidemiology.
