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ADDING SEMANTICS TO SPATIAL CONTENT-A LAND COVER SCENARIO

For successful implementation of geospatial information sharing platforms, we need solutions for overcoming syntactic and semantic ‘noise’ that may occur while sharing spatial data across communities, enterprises and application domains. For example, querying existing spatial data repositories is commonly based on thematic, spatial and temporal criteria. Semantic heterogeneity problems caused by ambiguity of thematic keywords pose great challenges for discovering appropriate spatial information. Over the last years, ontologies have been identified as solutions to overcome the challenges associated with spatial information discovery by adding semantics to (spatial) content. Therefore, an increasing number of (formalized) knowledge bases are now available. This is an important step towards enhancing information discovery experience, but it is not enough. Unfortunately, existing domain knowledge bases operate as standalone solutions and do not create the envisioned semantic synergies. This paper describes a conceptual framework flexible enough to integrate existing knowledge bases. It focuses mainly on the development of a lightweight ontology, rather than on technical implementation of it into discovery capabilities of existing repositories. Proposed framework utilizes lightweight ontologies for explicit specification of domain conceptualization and maps domain concepts against related concepts defined in other formalized concepts schemas. SKOS (Simple Knowledge Organization System) model is used to specify both hierarchical (general/specific or broader/narrower relations) and associative relations between concepts defined in different Knowledge Organization Systems (consistent schemata). Land cover datasets serve as running scenario across this paper. Challenges associated with domain ontology development are also discussed.