The semantic web is an emerging technology for expressing rich descriptions of a problem domain in the form of ontologies. An ontology provides a domain specific knowledge base for the communication and sharing of knowledge between various human and computer agents [1]. Many public health organizations have adopted syndromic surveillance systems but criteria for the selection of appropriate data sources, syndrome definitions, and applicable outbreak detection methods have not been established [2]. Application of semantic web technology to the field of syndromic surveil-lance has been seen to be successful in an experimental environment through the BioSTORM project at the SMI labs at the Stanford University School of Medicine [3]. The semantic web shows promise for providing a universal problem description layer that will allow for easier integration between heterogeneous data sources and problem solving techniques.
Objective
A syndromic surveillance system which uses a semantic web description layer is more extensible than existing systems. This will be shown through the application of appropriate software metrics, as well as a case based review that targets three major system design components.