Sensor knowledge representation with spatiotemporal annotation: An energy sensor ontology use case

In our smart planet, there are numerous sensors sensing almost everything around us and streaming the sensor data to different data collectors. Storing, categorizing and analyzing sensor data are the key challenging areas with a view to provide their proper usage. Semantic querying on such a deluge of sensor data set imposes another challenge. As queries can be spatial, temporal and thematic in nature, so providing relevant output to each category of queries requires proper understanding of the semantics of the data. Sensor ontologies and their data representation are in place to help understand the semantic to certain extent. Majority of work has focused more on thematic annotation rather spatial and temporal informations about sensors. In this paper, we discuss how to enrich sensor ontologies by incorporating concepts of TimeML and GML to help spatial and temporal analysis and queries.