Publication result detail

Event-Driven Architecture for Health Event Detection from Multiple Sources

DENECKE, K.; KIRCHNER, G.; DOLOG, P.; SMRŽ, P.; LINGE, J.; BACKFRIED, G.; DREESMAN, J.

Original Title

Event-Driven Architecture for Health Event Detection from Multiple Sources

English Title

Event-Driven Architecture for Health Event Detection from Multiple Sources

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

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.

English abstract

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.

Keywords

Epidemic Intelligence, Text Mining, Disease Surveillance, Event driven
architecture

Key words in English

Epidemic Intelligence, Text Mining, Disease Surveillance, Event driven
architecture

Authors

DENECKE, K.; KIRCHNER, G.; DOLOG, P.; SMRŽ, P.; LINGE, J.; BACKFRIED, G.; DREESMAN, J.

RIV year

2012

Released

31.08.2011

Publisher

IOS Press

Location

Oslo

ISBN

978-1-60750-805-2

Book

Proceedings of the XXIII International Conference of the European Federation for Medical Informatics (MIE 2011)

Pages from

160

Pages to

164

Pages count

5

BibTex

@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"
}