Sensors Tell More than They Sense: Modeling and Reasoning about Sensor Observations for Understanding Weather Events

Abstract

In this paper, we argue that sensors provide a better understanding of geographic events. They produce observations that reflect the natural events taking place at a particular location. The essential part of deriving information about geographic events from sensor observations is to formalize the relations between them. In this spirit, we develop an ontology to capture the relations between weather events and properties observed by sensors. A case study is investigated to illustrate how blizzard events can be formally represented in relation to a set of atmospheric properties observed by a weather station. Using the ontological structures, we define and implement rules to reason about blizzard events from hourly weather observations. We use the historical weather records from the Canadian Climate Archives database to evaluate our approach. The result includes an interactive timeline illustrating the events. The approach is evaluated in terms of reasoning and querying support against a local use. Keywords: Events, observations, ontology, query, rule-based representation and reasoning, sensors, weather, Open Geospatial Consortium (OGC), Semantic Web for Earth and Environmental Terminology (SWEET), Descriptive Ontology for Linguistic, Cognitive Engineering (DOLCE)