Converting Ontologies into DSLs

Authors João M. Sousa Fonseca, Maria João Varanda Pereira, Pedro Rangel Henriques



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Author Details

João M. Sousa Fonseca
Maria João Varanda Pereira
Pedro Rangel Henriques

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João M. Sousa Fonseca, Maria João Varanda Pereira, and Pedro Rangel Henriques. Converting Ontologies into DSLs. In 3rd Symposium on Languages, Applications and Technologies. Open Access Series in Informatics (OASIcs), Volume 38, pp. 85-92, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)
https://doi.org/10.4230/OASIcs.SLATE.2014.85

Abstract

This paper presents a project whose main objective is to explore the Ontological-based development of Domain Specific Languages (DSL), more precisely, of their underlying Grammar. After reviewing the basic concepts characterizing Ontologies and Domain-Specific Languages, we introduce a tool, Onto2Gra, that takes profit of the knowledge described by the ontology and automatically generates a grammar for a DSL that allows to discourse about the domain described by that ontology. This approach represents a rigorous method to create, in a secure and effective way, a grammar for a new specialized language restricted to a concrete domain. The usual process of creating a grammar from the scratch is, as every creative action, difficult, slow and error prone; so this proposal is, from a Grammar Engineering point of view, of uttermost importance. After the grammar generation phase, the Grammar Engineer can manipulate it to add syntactic sugar to improve the final language quality or even to add semantic actions. The Onto2Gra project is composed of three engines. The main one is OWL2DSL, the component that converts an OWL ontology into an attribute grammar. The two additional modules are Onto2OWL, converts ontologies written in OntoDL (a light-weight DSL to describe ontologies) into standard OWL, and DDesc2OWL, converts domain instances written in the DSL generated by OWL2DSL into the initial OWL ontology.
Keywords
  • ontology
  • OWL
  • RDF
  • languages
  • DSL
  • grammar

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