Um serviço de persistência de contexto e seleção contextualizada de documentos para a Arquitetura ClinicSpace

• Ano de defesa: 2011
• Autor(a) principal: Maran, Vinícius
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; BR; Ciência da Computação; UFSM; Programa de Pós-Graduação em Informática
• Palavras-chave em Português: Computação ubíqua na saúde; Sistemas de informação clínica; Seleção contextualizada; Persistência de contexto; Ubiquitous computing; Healthcare; Contextualized selection; Context persistence; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://repositorio.ufsm.br/handle/1/5387

Actual healthcare systems suffer from a high rate of rejection by the physicians who use these systems, because it is necessary that the users explicitly provide information constantly to these systems. This way, one of the biggest challenges for pervasive healthcare systems is to find a way to use context information of the environment in a simple and functional form between different computer systems. In the literature, ontologies are frequently used for the representation of context and have an important role in pervasive systems if used together with forms of persistence and retrieval of context information. To solve the mentioned problem, is under development an architecture called ClinicSpace which focuses on providing assistance to physicians in performing their daily tasks, using concepts defined in ubiquitous computing, which allows the system to to adapt constantly to the user and their needs. To make this, it is necessary that the system be capable of (i) store information of context and (ii) provide the documents frequently used by physicians, in an adapted way to the context of the tasks performed, and available anytime and anywhere (pervasiveness). This work describes the process of developing an integrated service ClinicSpace to architecture, which supports the use of context data and clinical documents in a distributed manner, and also allows the contextualized selection of clinical documents, using data from the context at the time of clinical information query.