Memorias de investigación
Artículos en revistas:
An Event Abstraction Layer for the Integration of Geosensor Data
Año:2014

Áreas de investigación
  • Ciencias de la computación y tecnología informática

Datos
Descripción
Time series of observations reflect the status of environmental properties. Variations in these properties can be considered as events when they potentially affect the stability of the monitored environment. Organisations dedicated to analyse environmental change use institutionalised descriptions of events to define the observable conditions under which events happen. This also applies to the methods used to classify and model changes in environmental monitoring. The heterogeneity of representations often causes interoperability problems when such communities exchange geospatial information. To enhance interoperability among diverse communities, it is required to develop models that do not restrict the representation of events, but allow integrating different perspectives on changes in the environment. The goal of the Event Abstraction Layer is to facilitate the analysis and integration of geosensor data by inferring events from time series of observations. For the analysis of geosensor data, we use event processing to detect event patterns in time series of observations. Spatiotemporal properties of the event are inferred from the geosensor location and the observation timestamps. For the data integration, we represent event-related information extracted from multiples sources under a common event model. Additionally, domain knowledge is modelled in a multilevel ontology structure.
Internacional
Si
JCR del ISI
Si
Título de la revista
International Journal of Geographical Information Science
ISSN
1365-8816
Factor de impacto JCR
Información de impacto
Volumen
28 issue 5
DOI
10.1080
Número de revista
5
Desde la página
1085
Hasta la página
1106
Mes
SIN MES
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Participantes
  • Autor: Alejandro Llaves Arellano UPM

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial