A Semantic Framework to Support Evolution and Interoperability
Arash Shaban-Nejad of the University of Tennessee Health Science Center in the U.S. will develop an analytic framework to help integrate dynamic surveillance data from multiple sources and health systems to support decision making for malaria elimination. Data on malaria is currently scattered in different formats across diverse organizations, making it difficult to access and use. An ontology is a web-based method that explicitly defines specific concepts using logical rules and constraints, and can be used to capture and combine information from numerous sources into a formal framework. They will analyze existing malaria data sources such as Mapping Malaria Risk in Africa (MARA) across selected African countries with different languages including Uganda and Gabon, and use it to generate a service ontology that enables data integration, and implement a semantic web service that can also be used to access the data.