Structuring an event ontology for disease outbreak detection.

Ai Kawazoe,Mika Shigematsu,Nigel Collier,Hutchatai Chanlekha

doi:10.1186/1471-2105-9-s3-s8

Ai Kawazoe, Mika Shigematsu + Show 2 more

Open Access

https://doi.org/10.1186/1471-2105-9-s3-s8

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Abstract

BackgroundThis paper describes the design of an event ontology being developed for application in the machine understanding of infectious disease-related events reported in natural language text. This event ontology is designed to support timely detection of disease outbreaks and rapid judgment of their alerting status by 1) bridging a gap between layman's language used in disease outbreak reports and public health experts' deep knowledge, and 2) making multi-lingual information available.Construction and contentThis event ontology integrates a model of experts' knowledge for disease surveillance, and at the same time sets of linguistic expressions which denote disease-related events, and formal definitions of events. In this ontology, rather general event classes, which are suitable for application to language-oriented tasks such as recognition of event expressions, are placed on the upper-level, and more specific events of the experts' interest are in the lower level. Each class is related to other classes which represent participants of events, and linked with multi-lingual synonym sets and axioms.ConclusionsWe consider that the design of the event ontology and the methodology introduced in this paper are applicable to other domains which require integration of natural language information and machine support for experts to assess them. The first version of the ontology, with about 40 concepts, will be available in March 2008.

Highlights

This paper describes the design of an event ontology being developed for application in the machine understanding of infectious disease-related events reported in natural language text
We consider that the design of the event ontology and the methodology introduced in this paper are applicable to other domains which require integration of natural language information and machine support for experts to assess them
Application of BioCaster Event Ontology (BCEO) BCEO described so far will be applied for 1) annotating/ grounding text mentions of events, 2) translation of terms which denote events, 3) modelling of public health experts' knowledge used to judge the alerting relevance of disease-related events. (1) is important in making a basis for automatic recognition of varieties of event expressions in disease outbreak reports, in addition to the traditional named entities. (2) is necessary to provide disease outbreak information in users' native languages, and grasp relationship between reports written in different languages

Summary

Conclusions

We consider that the design of the event ontology and the methodology introduced in this paper are applicable to other domains which require integration of natural language information and machine support for experts to assess them. The first version of the ontology, with about 40 concepts, will be available in March 2008

Background

Utility and discussion

Conclusion

Bach E

Findings

10. Pelletier FJ