Rule‐Based Discovery in Spatial Data Infrastructure

Abstract Answering questions based on spatial data is becoming increasingly important in a variety of domains. Often the required data are distributed and heterogeneous, and several data sources need to be combined in order to derive the information required by a user. Spatial data infrastructures (SDIs) are aimed at making the discovery and access to distributed geographic data more efficient. However, the catalogue services currently used in SDIs for discovering geographic data do not allow expressive queries and do not take into account that more than one data source might be required to answer a question. In this paper, we present a methodology that uses rules for both the discovery of data sources and, based on the discovered data, answering user queries in SDIs. We illustrate how this methodology allows inferences that use relationships between individuals and the combination of data from different sources, thus overcoming some of the limitations of other Semantic Web approaches that are based on Description Logics. The approach is illustrated by an example from the domain of disaster management.