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The description, localization and effective reuse of software patterns and systems of patterns can be approached through an ontology-based formalism. An ontology is an explicit specification of objects, concepts and entities of an area of interest, besides the relationships between these concepts expressed through axioms. This work introduces ONTOPATTERN, an ontology that represents knowledge about how patterns are described and about their relationships in a pattern system. Patterns are included as instances of classes in the ontology, thus turning ONTOPATTERN a knowledge base where concepts are semantically related and where searches and inferences can be made thus facilitating the understanding and reuse of patterns. The use of ONTOPATTERN is illustrated through an example on the construction of a multi-agent framework. IntroductionIn spite of the large number of software pattern collections and systems [1][2][4][7][11][23][25][28] already available, there is the need of a formalism to facilitate their description, localization and effective reuse in the development of software applications. This can be approached through ontologies.

This article proposes a process for automatic population of ontologies from text that applies natural language processing and information extraction techniques to acquire and classify ontology instances. The work is part of HERMES, an FCT/CAPES research project looking for techniques and tools for automating the process of ontology learning and population. Two experiments using a legal and a tourism corpora were conducted in order to evaluate it. The results indicate that our approach can extract and classify instances with high effectiveness with the additional advantage of domain independence.

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