An Ontology-Based Framework for Geographic Data Integration

Abstract

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.

An Ontology-Based Framework for Heterogeneous Data Sources Integration

“…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.…”

“…In our approach, the process of answering a query posed on the mediated schema consists of three steps: (i) Semantic rewriting. The user's query is decomposed into a set of elementary sub-queries over the application ontologies using the algorithm proposed in [3], and it is generated a semantic execution plan (SEP), which specifies how the results of these sub-queries are combined to obtain an intermediate result. This step is performed using the mediated mappings and the global axioms (ii) Optimization.…”

“…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.…”

Building a Geographical Ontology for the Nile River

“…Shawn Bowers et al [12] describe a novel approach to construct large ontologies of ecological terms (classes and properties) which allows ecologists to use common spreadsheet tools to describe different aspects of ontology. Many other GIR researchers, who are recognized in literature such as [13], [14], [15] and [16] use ontologies to assist spatial search.…”

Genômica translacional: integrando dados clínicos e biomoleculares

“…Mapeamentos semânticos são utilizados para definir como dados de uma fonte são traduzidos para dados de uma outra fonte, ou alternativamente, como uma consulta a uma fonte pode ser reescrita para uma consulta equivalente em outra (VIDAL et al, 2009 …”