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.
Llaves et al. REF investigates how to infer and represent events from time series of in situ sensor observations.
An event abstraction layer for the integration of geosensor data
International Journal of Geographical Information Science
Computer Science