Ontologies have been extensively used to model domain-specific knowledge. Recent research has applied ontologies to enhance the discovery and retrieval of geographic data in Spatial Data Infrastructures (SDIs). However, in those approaches it is assumed that all the data required for answering a query can be obtained from a single data source. In this work, we propose an ontology-based framework for the integration of geographic data. In our approach, a query posed on a domain ontology is rewritten into sub-queries submitted over multiples data sources, and the query result is obtained by the proper combination of data resulting from these sub-queries. We illustrate how our framework allows the combination of data from different sources, thus overcoming some limitations of other ontology-based approaches. Our approach is illustrated by an example from the domain of aeronautical flights.

No abstract

No abstract

The Proposed FrameworkOntologies have been extensively used to model domain-specific knowledge. The main reason for this success is due to their capability to be at the "semantic" level, away from data structures and implementation strategies. In addition, ontology formalisms have allowed certain kinds of reasoning to be automated within a reasonable time complexity. Due to ontology data independence and automated reasoning, ontologies are well suited for integrating heterogeneous databases, enabling interoperability among disparate systems, and specifying interfaces to independent, knowledge-based services.Recent research has used ontologies for specifying the mediated schema in the context of data integration [2,3]. An important challenge in ontology-based data integration systems is the problem of rewriting a query specified in terms of the domain ontology into queries that can be answered by the individual data sources. Reasoning is used to determine whether existing ontology concepts (describing the local data sources) are a match for the user's query and to query rewrite. Description Logics can be used to describe relationships between data sources [1] and to provide more flexible mechanisms for semantic query rewriting needed in such systems [2], Despite those approaches, little work has been done focusing on the optimization of querying processing in a ontology-based data integration system.In this work, we propose an ontology-based framework for integration of heterogeneous data sources, comprising the benefits of ontologies to make the semantic integration; and of ontological reasoning to discard sub-queries that are not consistent and to infer additional relations between concepts. Figure 1 describes the main components of the proposed architecture. The mediated schema is represented by a domain ontology (DO), which provides a conceptual representation of the application domain (a global shared vocabulary).