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Statements

Subject Item
n2:RIV%2F00216305%3A26230%2F11%3APU96053%21RIV12-MSM-26230___
rdf:type
n11:Vysledek skos:Concept
dcterms:description
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. 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.
dcterms:title
Event-Driven Architecture for Health Event Detection from Multiple Sources Event-Driven Architecture for Health Event Detection from Multiple Sources
skos:prefLabel
Event-Driven Architecture for Health Event Detection from Multiple Sources Event-Driven Architecture for Health Event Detection from Multiple Sources
skos:notation
RIV/00216305:26230/11:PU96053!RIV12-MSM-26230___
n11:predkladatel
n17:orjk%3A26230
n3:aktivita
n10:S n10:P n10:Z
n3:aktivity
P(7E10054), S, Z(MSM0021630528)
n3:dodaniDat
n16:2012
n3:domaciTvurceVysledku
n8:1574582
n3:druhVysledku
n7:D
n3:duvernostUdaju
n15:S
n3:entitaPredkladatele
n23:predkladatel
n3:idSjednocenehoVysledku
198437
n3:idVysledku
RIV/00216305:26230/11:PU96053
n3:jazykVysledku
n4:eng
n3:klicovaSlova
Epidemic Intelligence, Text Mining, Disease Surveillance, Event driven architecture
n3:klicoveSlovo
n9:Event%20driven%20architecture n9:Disease%20Surveillance n9:Epidemic%20Intelligence n9:Text%20Mining
n3:kontrolniKodProRIV
[4DB08ED6F7E3]
n3:mistoKonaniAkce
Oslo
n3:mistoVydani
Oslo
n3:nazevZdroje
Proceedings of the XXIII International Conference of the European Federation for Medical Informatics (MIE 2011)
n3:obor
n12:IN
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
7
n3:projekt
n5:7E10054
n3:rokUplatneniVysledku
n16:2011
n3:tvurceVysledku
Kirchner, Göran Dreesman, Johannes Backfried, Gerhard Linge, Jens Denecke, Kerstin Dolog, Peter Smrž, Pavel
n3:typAkce
n22:WRD
n3:zahajeniAkce
2011-08-28+02:00
n3:zamer
n14:MSM0021630528
s:numberOfPages
5
n18:hasPublisher
IOS Press
n19:isbn
978-1-60750-805-2
n20:organizacniJednotka
26230