Publication Details
Event-Driven Architecture for Health Event Detection from Multiple Sources
Kirchner Göran
Dolog Peter
Smrž Pavel, doc. RNDr., Ph.D. (DCGM)
Linge Jens
Backfried Gerhard
Dreesman Johannes
Epidemic Intelligence, Text Mining, Disease Surveillance, Event driven architecture
Early detection of potential health threats is crucial for taking actions in time. It is unclear in which information source an event is reported first and, information from various sources can be complementing. Thus, it is important to search for information in a very broad range of sources. Furthermore, real-time processing is necessary to deal with the huge amounts of incoming data in time. Event-driven architectures are designed to address such challenges. This will be shown in this paper by presenting the architecture of a public health surveillance system that follows this style. Starting from concrete user requirements and scenarios, we introduce the architecture with its components for content collection, data analysis and integration. The system will allow for the monitoring of events in real-time as well as retrospectively.
@inproceedings{BUT76355,
author="Kerstin {Denecke} and Göran {Kirchner} and Peter {Dolog} and Pavel {Smrž} and Jens {Linge} and Gerhard {Backfried} and Johannes {Dreesman}",
title="Event-Driven Architecture for Health Event Detection from Multiple Sources",
booktitle="Proceedings of the XXIII International Conference of the European Federation for Medical Informatics (MIE 2011)",
year="2011",
pages="160--164",
publisher="IOS Press",
address="Oslo",
isbn="978-1-60750-805-2"
}