Um perfil de metadados Dublin Core para documentar padrões de análise em uma infraestrutura de reuso

• Ano de defesa: 2012
• Autor(a) principal: Vegi, Lucas Francisco da Matta
• Orientador(a): Lisboa Filho, Jugurta
• Banca de defesa: Villela, Regina Maria Maciel Braga
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Viçosa
• Programa de Pós-Graduação: Mestrado em Ciência da Computação
• Departamento: Metodologias e técnicas da Computação; Sistemas de Computação
• País: BR
• Palavras-chave em Português: Padrões de análise; Reutilização; Padrões de metadados; Dublin Core; Web Semântica; Linked Data
• Palavras-chave em Inglês: Analysis patterns; Reuse; Metadata standards; Dublin Core, Semantic Web; Linked Data
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://locus.ufv.br/handle/123456789/2636

Analysis patterns are reusable computational artifacts, aimed at the analysis stage of the development process of software. Although the analysis patterns can facilitate the work of analysts and developers by the reuse of proven useful and tested ideas, the access to them is still poor because of the way they are usually described and made available. The potential for reuse of analysis patterns is impaired because there is not a standardized way to document this kind of patterns, and in addition, the analysis patterns are usually made available by means not processable by machine, thereby complicating their retrieval. The general objective of this master s thesis was to reduce deficiencies in documentation and provision of analysis patterns, supporting cataloging and encouraging the reuse of these patterns by means of an Analysis Patterns Reuse Infrastructure (APRI). This infrastructure, analogous to a Spatial Data Infrastructure (SDI), comprises a repository of analysis patterns documented through a specific metadata profile and accessed via Web services. Among the specific objectives of this master's thesis is the development of a machine-processable metadata profile suitable to the documentation of analysis patterns. This metadata profile, called Dublin Core Application Profile to Analysis Patterns (DC2AP), was proposed to be integrated into the architecture of an APRI. DC2AP was described by RDF files identified via URI, thus providing Linked Data that allow document and provide analysis patterns interpretable by machine. The use of DC2AP to document analysis patterns allows a more adequate retrieval of these patterns by means of computerized search engines, thereby increasing the potential for reuse of analysis patterns.