The epidemiology ontology: an ontology for the semantic annotation of epidemiological resources

Catia Pesquita,João D Ferreira,Mário J Silva,Francisco M Couto

doi:10.1186/2041-1480-5-4

Abstract

BackgroundEpidemiology is a data-intensive and multi-disciplinary subject, where data integration, curation and sharing are becoming increasingly relevant, given its global context and time constraints. The semantic annotation of epidemiology resources is a cornerstone to effectively support such activities. Although several ontologies cover some of the subdomains of epidemiology, we identified a lack of semantic resources for epidemiology-specific terms. This paper addresses this need by proposing the Epidemiology Ontology (EPO) and by describing its integration with other related ontologies into a semantic enabled platform for sharing epidemiology resources.ResultsThe EPO follows the OBO Foundry guidelines and uses the Basic Formal Ontology (BFO) as an upper ontology. The first version of EPO models several epidemiology and demography parameters as well as transmission of infection processes, participants and related procedures. It currently has nearly 200 classes and is designed to support the semantic annotation of epidemiology resources and data integration, as well as information retrieval and knowledge discovery activities.ConclusionsEPO is under active development and is freely available at https://code.google.com/p/epidemiology-ontology/. We believe that the annotation of epidemiology resources with EPO will help researchers to gain a better understanding of global epidemiological events by enhancing data integration and sharing.

Highlights

Epidemiology is a data-intensive and multi-disciplinary subject, where data integration, curation and sharing are becoming increasingly relevant, given its global context and time constraints
Whenever an equivalent class was present in Transmission Ontology (TRANS) we imported it, but used the label and definition from the Dictionary of Epidemiology (DoE) as editor preferred label and definition, which resulted in reusing 14 TRANS classes, for a total of 21 transmission of infection types modeled in Epidemiology Ontology (EPO)
These classes are organized in single inheritance, in up to five levels, increasing the granularity level given by TRANS by two levels, and widening its scope by including classes for the participants in the transmission of infection process

Summary

Introduction

Epidemiology is a data-intensive and multi-disciplinary subject, where data integration, curation and sharing are becoming increasingly relevant, given its global context and time constraints. Consider the following example: a research team is building a model for herd immunity in populations where a measles vaccine can be administered To achieve this, they need data on measles incidence rates and vaccination rates in different populations/locations over time, as well as other parameters, such as birth rate, factors influencing vaccination (e.g. legal frame, income and education level of parents), transmission mode and secondary attack rate (i.e. the number of cases of an infection that occur among contacts within the incubation period following exposure to a primary case in relation to the total number of exposed contacts). Resources that do not refer to measles, but to other typical childhood diseases with the same transmission mode can very well be of interest to extract parameters for the measles herd immunity model

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Conclusion