Publication 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

conference paper

Language

en

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

RIV year

2011

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)

Edition

NEUVEDEN

Edition number

NEUVEDEN

Pages from

160

Pages to

164

Pages count

5

Documents

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",
  annote="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.",
  address="IOS Press",
  booktitle="Proceedings of the XXIII International Conference of the European Federation for Medical Informatics (MIE 2011)",
  chapter="76355",
  edition="NEUVEDEN",
  howpublished="print",
  institution="IOS Press",
  year="2011",
  month="august",
  pages="160--164",
  publisher="IOS Press",
  type="conference paper"
}