Administrando Ontologías Grandes y Altamente Expresivas Mediante OWLAPI

• Autores: Manuel Enrique Puebla Martínez, Alfredo Javier Simón Cuevas, José Manuel Perea Ortega , Yanet Espinal Martín
• Localización: Revista Cubana de Ciencias Informáticas, ISSN-e 2227-1899, Vol. 15, Nº. 3, 2021
• Idioma: español
• Títulos paralelos:
  • Managing large and highly expressive ontologies through OWLAPI
• Enlaces
  • Texto completo
• Resumen
  • español

    La mayoría de las herramientas de código abierto para administrar y razonar sobre ontologías grandes requieren cargar previamente toda la ontología en la memoria principal para realizar operaciones de inferencia. Esto es un inconveniente cuando los recursos de hardware son limitados y se requiere administrar ontologías geográficas con millones de datos (instancias), debido a la alta complejidad espacial y temporal de los algoritmos utilizados por los razonadores basados en memoria. Este artículo presenta una extensión de OWLAPI para administrar y razonar sobre grandes ontologías geográficas en cualquier perfil de OWL2. La contribución principal es la reducción del uso de la memoria principal por parte de OWLAPI, pues solo una parte de la ontología es cargada en memoria principal y no todo el archivo OWL. Dos grandes geo-ontologías de diferentes áreas geográficas se gestionaron utilizando la solución propuesta con fines de demostración. Los resultados obtenidos demuestran la viabilidad de la propuesta para administrar grandes ontologías geográficas en OWL2 mediante el uso de OWLAPI y recursos de hardware limitados.

  • English

    Most of the existing open-source tools to manage and reason on large ontologies require previously loading the entire ontology in main memory to perform inference operations. This is a drawback when limited hardware resources are available and it is required to manage geographic ontologies with millions of data (instances), due to the high spatial and temporal complexity of the algorithms used by memory-based reasoners. This paper presents an extension of the OWLAPI to manage and reason on large geographic ontologies in any OWL2 profile. The main contribution is the reduction of the main memory usage by the OWLAPI, thus allowing loading only part of the ontology and not the entire OWL file. Two large geo-ontologies from different geographical areas were managed by using the proposed solution for demonstration purposes. The obtained results demonstrate the viability of the proposal to manage large geographic ontologies in OWL2 by using OWLAPI and limited hardware resources.

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