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Automated Large Geographic Ontologies Generation Method from Spatial Databases

  • Manuel E. Puebla-Martínez
  • José M. Perea-OrtegaEmail author
  • Alfredo Simón-Cuevas
  • Francisco P. Romero
  • José A. Olivas Varela
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1029)

Abstract

Ontologies have emerged as an important component in Information Systems and, specifically, in Geographic Information Systems, where they play a key role. However, the creation and maintenance of geographic ontologies can become an exhausting work due to the rapid growth and availability of spatial data, which are provided through relational databases most times. For this reason there has been an increasing interest in the automatic generation of geographic ontologies from relational databases in recent years. This work describes an automatic method to generate a geographic ontology from the spatial data provided by a relational database. The importance and originality of this study lie in that it is able to model two main aspects of a spatial database in the generated ontology: (1) The three main types of spatial data (point, line and polygon) are modelled as a data property and not as an object property. (2) Four data integrity constraints: First Normal Form, Not Null, Unique and Primary Key. Another contribution of our proposal is related to the support for generating large ontologies, which are not usually supported by traditional tools of ontological engineering such as Protégé or OWL API. Finally, some experiments were conducted in order to show the effectiveness of the proposed method.

Keywords

Spatial database Geographic ontology Automatic generation of ontology Data integrity constraints OWL2 

Notes

Acknowledgments

This work has been partially supported by FEDER and the State Research Agency (AEI) of the Spanish Ministry of Economy and Competition under grant MERINET: TIN2016-76843-C4-2-R (AEI/FEDER, UE).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Universidad de las Ciencias InformáticasLa HabanaCuba
  2. 2.Universidad de ExtremaduraBadajozSpain
  3. 3.Universidad Tecnológica de La Habana José Antonio EcheverríaLa HabanaCuba
  4. 4.Universidad de Castilla-La ManchaCiudad RealSpain

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