Publication Details
Event-Driven Architecture for Health Event Detection from Multiple Sources
Kirchner Göran (RKI)
Dolog Peter (AAU)
Smrž Pavel, doc. RNDr., Ph.D. (DCGM FIT BUT)
Linge Jens (JRC)
Backfried Gerhard (SAIL LABS Technology AG)
Dreesman Johannes (NLGA)
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{FITPUB9614, author = "Kerstin Denecke and G{\"{o}}ran Kirchner and Peter Dolog and Pavel Smr\v{z} and Jens Linge and Gerhard Backfried and Johannes Dreesman", title = "Event-Driven Architecture for Health Event Detection from Multiple Sources", pages = "160--164", booktitle = "Proceedings of the XXIII International Conference of the European Federation for Medical Informatics (MIE 2011)", year = 2011, location = "Oslo, NO", publisher = "IOS Press", ISBN = "978-1-60750-805-2", language = "english", url = "https://www.fit.vut.cz/research/publication/9614" }