Keywords
sensor data; knowledge acquisition; knowledge representation; environmental monitoring; situation awareness; wavellite
Location
Session F5: Advances in Environmental Software Systems
Start Date
17-6-2014 3:40 PM
End Date
17-6-2014 5:20 PM
Abstract
Situation assessment, i.e. the process of achieving situation awareness, is common in environmental monitoring, where assessment occurs predominantly on sensor data and awareness is for the state of environmental phenomena. For a particular location, an environmental monitoring system may measure and compute mean hourly PM2.5 concentration to acquire knowledge for situations of unhealthy exposure by humans to ambient air; it may measure aerosol particle size distribution to acquire knowledge for situations of atmospheric new particle formation; it may measure road-pavement vibration to acquire knowledge for traffic. The process can be divided in four generic sub processes, namely data acquisition, data processing, knowledge acquisition and extraction, and knowledge representation and reasoning. We outline an ontology for the process. It aligns and specializes the generic concepts of several upper ontologies. The ontology could form a building block in the discovery and query of situational knowledge acquired and represented by distributed environmental monitoring systems, from heterogeneous sensor data and for diverse environmental phenomena, in time and space.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
Towards an Ontology for Situation Assessment in Environmental Monitoring
Session F5: Advances in Environmental Software Systems
Situation assessment, i.e. the process of achieving situation awareness, is common in environmental monitoring, where assessment occurs predominantly on sensor data and awareness is for the state of environmental phenomena. For a particular location, an environmental monitoring system may measure and compute mean hourly PM2.5 concentration to acquire knowledge for situations of unhealthy exposure by humans to ambient air; it may measure aerosol particle size distribution to acquire knowledge for situations of atmospheric new particle formation; it may measure road-pavement vibration to acquire knowledge for traffic. The process can be divided in four generic sub processes, namely data acquisition, data processing, knowledge acquisition and extraction, and knowledge representation and reasoning. We outline an ontology for the process. It aligns and specializes the generic concepts of several upper ontologies. The ontology could form a building block in the discovery and query of situational knowledge acquired and represented by distributed environmental monitoring systems, from heterogeneous sensor data and for diverse environmental phenomena, in time and space.
