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Epidemiology research is a truly multidisciplinary subject, relying on areas of knowledge as diverse as medicine, biology, statistics, sociology and geography.1 The creation of large-scale epidemiological models and the development of effective model-based prediction methods can only be achieved if efficient data collection techniques based on reliable policies for data sharing between research communities and health authorities are adopted.2 As a research domain that so strongly depends on heterogeneous data from diverse origins, epidemiology greatly requires a proper integrative framework to cope with its inherent multidisciplinarity.
One promising way to meet these requirements is the adoption by the epidemiology community of Semantic Web technologies. The Semantic Web is a vision of information management and sharing that promotes intelligent access to data on the world wide web, both by human beings and by computers.3 The adoption of the Semantic Web is not new in biomedical research: for instance, in molecular biology, it has been applied in the past with intent to create successful applications. One of these is GoPubMed, a platform that enables a deep and structured exploration of PubMed abstracts4; another one is a method to identify gene functions associated with specific biological phenomena.5
The remainder of this manuscript will illustrate the advantages of adopting this paradigm for epidemiological studies, together with a brief introduction of standard Semantic Web concepts and practices, that could be useful for current and prospective epidemiologists. We also present the Epidemic Marketplace, a case study for storing and describing epidemiological resources following the Semantic Web vision.
The Semantic Web vision
The world wide web is, by itself, an extremely useful content-sharing platform, but the content of its resources is not expressed through a common data format and is mainly directed at human users. To achieve machine-readability, the Semantic Web perceives information as resources …