Improving geographic information retrieval in spatial data infrastructures

In recent years, spatial data infrastructures (SDIs) have gained great popularity as a solution to facilitate interoperable access to geospatial data offered by different agencies. In order to enhance the data retrieval process, current infrastructures usually offer a catalog service. Nevertheless,...

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Bibliographic Details
Published in:GeoInformatica 2014-10, Vol.18 (4), p.793-818
Main Authors: de Andrade, Fabio Gomes, de Souza Baptista, Cláudio, Davis, Clodoveu Augusto
Format: Article
Language:English
Subjects:
Computer Science
Data analysis
Data retrieval
Data Structures and Information Theory
Earth and Environmental Science
Geographic information systems
Geographical Information Systems/Cartography
Geography
Geospatial data
Information retrieval
Information Storage and Retrieval
Infrastructure
Multimedia Information Systems
Query processing
Ranking
Semantics
Temporal logic
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Summary:In recent years, spatial data infrastructures (SDIs) have gained great popularity as a solution to facilitate interoperable access to geospatial data offered by different agencies. In order to enhance the data retrieval process, current infrastructures usually offer a catalog service. Nevertheless, such catalog services still have important limitations that make it difficult for users to find the geospatial data that they are interested in. Some current catalog drawbacks include the use of a single record to describe all the feature types offered by a service, the lack of formal means to describe the semantics of the underlying data, and the lack of an effective ranking metric to organize the results retrieved from a query. Aiming to overcome these limitations, this article proposes SESDI (Semantically-Enabled Spatial Data Infrastructures), which is framework that reuses techniques of classic information retrieval to improve geographic data retrieval in a SDI. Moreover, the framework proposes several ranking metrics to solve spatial, semantic, temporal and multidimensional queries.
ISSN:1384-6175
1573-7624
DOI:10.1007/s10707-014-0202-x