On Implementing Temporal Query Answering in DL-Lite (extended abstract)

Temporal information plays a central role in many applications of ontology-based data access (OBDA). For example, knowledge about the past is usually kept in patient records, and collected by companies or scientific projects as MesoWest4 , focusing on weather data. Such applications obviously benefit from using ontologies for data integration and access (e.g., the wind force ‘Storm’ on the well-known Beaufort Wind Force Scale is equally characterized by wind speed and wave height, which can be represented by a general concept inclusion as HighWindSpeed t HighWaves v Storm). Temporal knowledge is however not taken into account by systems implementing OBDA, in general. Though, assuming that we consider several weather stations’ data of the past 24 hours, a query such as the following could be interesting: “Get the heritage sites that are nearby a weather station, for which at some time in the past (24 hours) a danger of a hurricane was detected, since then, the wind force has been continuously very high, and it increased considerably during the two latest times of observation.”