Current Approaches and Future Trends of Ontology-Driven Geographic Integration

Current Approaches and Future Trends of Ontology-Driven Geographic Integration

Agustina Buccella (Universidad Nacional del Comahue, Argentina) and Alejandra Cechich (Universidad Nacional del Comahue, Argentina)
DOI: 10.4018/978-1-60566-242-8.ch052
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Currently there are many domain areas in Computer Science interested in the integration of various information sources. Federated Databases, Semantic Web, and Automated Web Services are some of them. Particularly in the geographic information area, newer and better technologies and devices are being created in order to capture a large amount of information about Earth. All of this geographic information is analyzed and stored at various levels of detail in Geographic Information Systems (GISs), possibly distributed on the Web. Then a fast search for geographic information on the Web will return several links representing parts of our world. But what happens when someone needs information that is divided into more than one system? For example, information about rivers in a country can be obtained by querying two or more systems. Although distribution of information is one of the main problems, there are some others; these systems have been developed by various entities with different points of view and vocabularies, and here is when face heterogeneity problems arise. They are encountered in every communication between interoperating systems where interoperability refers to interaction between information from various sources involving the task of data integration to combine data.
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Gis Integration: Basic Concepts

The concept of data integration is concerned with unifying data that share some common semantics but originate from unrelated sources. In every integration process, heterogeneity is one of the most common problems. Let us consider two systems sharing data representing rivers, which can be an example to clarify different types of heterogeneity problems (Hakimpour, 2003):

Key Terms in this Chapter

Federated Information System (FIS): A set of autonomous, distributed, and heterogeneous information systems that are operated together to generate a useful answer to users.

Data Integration: Process of unifying data that share some common semantics but originate from unrelated sources.

Ontology Merging: The process of generating the creation of a new ontology from two or more existing ontologies with overlapping parts, which can be either virtual or physical.

Ontology: Provides a vocabulary to represent and communicate knowledge about the domain and a set of relationships containing the terms of the vocabulary at a conceptual level.

Semantic Heterogeneity: Each information source has a specific vocabulary according to its understanding of the world. The different interpretations of the terms within each of these vocabularies cause the semantic heterogeneity.

Geographic information: Information about objects or phenomena that are associated with a location relative to the surface of Earth. A special case of spatial information.

Ontology Mapping: The process of relating similar (according to some metric) concepts or relations from various sources to each other by an equivalence relation. A mapping results in a virtual integration.

Geographic Information System (GIS): A computer-based system to efficiently model, capture, store, manipulate, query, retrieve, analyze, and visualize information, where part of the information is of a geographic nature. It is generally based on a structured database that describes the world in geographic terms.

Heterogeneous Information System: A set of information systems that differs in syntactical or logical aspects, such as hardware platforms, data models, or semantics.

Spatial Data: Any information about the location and shape of, and relationships among geographic features. This includes remotely sensed data as well as map data.

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