The next generation of the web, the Semantic Web, integrates distributed web resources from various domains by allowing data (instantial and ontological data) to be shared and reused across applications, enterprise and community boundaries based on the Resource Description Framework (RDF). Nevertheless, the RDF was not developed for casual users who are unfamiliar with the RDF but interested in data represented using RDF. NLG may be a possible solution to bridging the gap between the casual users and RDF data, but the cost of separately applying fine grained NLG techniques for every domain in the Semantic Web would be extremely high, and hence not realistic.

Thesis (Ph.D.)--Aberdeen University, 2008. / Title from web page (viewed on Mar. 23, 2009). Includes bibliographical references.

AGUIA é uma aplicação web front-end, desenvolvida para gerenciar dados clínicos, demográficos e biomoleculares de pacientes coletados durante os ensaios clínicos gastrointestinais no MD Anderson Cancer Center. A diversidade de metodologias envolvidas na triagem de pacientes e no processamento da amostra traz uma heterogeneidade dos tipos de dados correspondentes. Sendo assim, estes devem ser baseados em uma arquitetura orientada a recurso que transforma dados heterogêneos em dados semânticos, mais especificamente em RDF (Resource Description Framework - Estrutura para a descrição de recursos). O banco de dados escolhido foi o S3DB, por este ter cumprido os requisitos necessários de transformação dos dados heterogêneos de diferentes fontes em RDF, distinguindo explicitamente a descrição do domínio e sua instanciação, permitindo simultaneamente a contínua edição de ambos. Além disso, ele usa um protocolo REST, e é de código aberto e domínio público o que facilita o desenvolvimento e divulgação. Contudo, por mais abrangente e flexível, um formato de web semântica pode por si só, não abordar a questão de representar o conteúdo de uma forma que faça sentido para especialistas do domínio. Assim, o objetivo do trabalho aqui descrito foi identificar um conjunto adicional de descritores que forneceu as especificações para a interface gráfica do usuário. Esse objetivo foi perseguido através da identificação de um formalismo que faz uso do esquema RDF para permitir a montagem automática de interfaces gráficas de uma forma significativa. Um modelo RDF generalizado foi, portanto, definido de tal forma que as mudanças nos descritores gráficos sejam automaticamente e imediatamente refletidas na configuração da aplicação web do cliente, que também está disponível neste trabalho. Embora os padrões de design identificados reflitam e beneficiem os requisitos específicos de interagir com os dados gerados pelos ensaios clínicos, a expectativa é que eles contenham pistas para uma solução de propósito geral. Em particular, sugere-se que os padrões mais úteis identificados pelos utilizadores deste sistema sejam suscetíveis de serem reutilizáveis para outras fontes de dados, ou pelo menos para outros bancos de dados semânticos de ensaios clínicos. / AGUIA is a web application front-end originally developed to manage clinical, demographic and biomolecular patient data collected during gastrointestinal clinical trials at MD Anderson Cancer Center. The diversity of methodologies involved in patient screening and sample processing, brings corresponding heterogeneity of data types. Thus, this data must be based on a Resource Oriented Architecture that transforms heterogeneous data in semantic data, most specifically in RDF (Resource Description Framework). The database chosen was a S3DB, because it met the necessary requirements of transforming heterogeneous data from different sources in RDF, explicitly distinguishing the description of the domain from its instantiation, while allowing for continuous editing of both. Furthermore, it uses a REST protocol, and is open source and in the public domain which facilitates development and dissemination. Nevertheless, comprehensive and flexible a semantic web format may be, it does not by itself address the issue of representing content in a form that makes sense for domain experts. Accordingly, the goal of the work described here was to identify an additional set of descriptors that provide specifications for the graphic user interface. That goal was pursued by identifying a formalism that makes use of the RDF schema to enable automatic assembly of graphic user interfaces in a meaningful manner. A generalized RDF model was therefore defined such that changes in the graphic descriptors are automatically and immediately reflected into the configuration of the client web browser interface application, which is also made available with this report. Although the design patterns identified reflect, and benefit, from the specific requirements of interacting with data generated by clinical trials, the expectation is that they contain clues for a general purpose solution. In particular, it is suggested that the most useful patterns identified by the users of this system are susceptible to being reusable for other data sources, or at least for other clinical trial semantic web data stores.

The Semantic Web, or the Web of Data, promotes common data formats for representing structured data and their links over the web. RDF is the defacto standard for semantic data where it provides a flexible semi-structured model for describing concepts and relationships. RDF datasets consist of entries (i.e, triples) that range from thousands to Billions. The astronomical growth of RDF data calls for scalable RDF management and query processing strategies. This dissertation addresses efficient query processing over web-scale RDF data. The first contribution is WORQ, an online, workload-driven, RDF query processing technique. Based on the query workload, reduced sets of intermediate results (or reductions, for short) that are common for specific join pattern(s) are computed in an online fashion. Also, we introduce an efficient solution for RDF queries with unbound properties. The second contribution is SPARTI, a scalable technique for computing the reductions offline. SPARTI utilizes a partitioning schema, termed SemVP, that enables efficient management of the reductions. SPARTI uses a budgeting mechanism with a cost model to determine the worthiness of partitioning. The third contribution is KC, an efficient RDF data management system for the cloud. KC uses generalized filtering that encompasses both exact and approximate set membership structures that are used for filtering irrelevant data. KC defines a set of common operations and introduces an efficient method for managing and constructing filters. The final contribution is semantic filtering where data can be reduced based on the spatial, temporal, or ontological aspects of a query. We present a set of encoding techniques and demonstrate how to use semantic filters to reduce irrelevant data in a distributed setting.

The Resource Description Framework (RDF) is the logical data model of the Semantic Web. RDF encodes information as a directed graph using a set of labeled edges known formally as resource-property-value statements or, in common usage, as RDF triples or simply triples. Values recorded in RDF triple form are either Universal Resource Identifiers (URIs) or literals. The use of URIs allows links between distributed data sources, which enables a logical model of data as a graph spanning the Internet. SPARQL is a standard SQL-like query language on RDF triples. This report describes the translation of SPARQL queries to equivalent SQL queries operating on a relational representation of RDF triples, and the physical optimization of that representation using the IBM DB2 relational database management system. Performance was evaluated using the Berlin SPARQL Benchmark. The results show that the implementation can perform well on certain queries, but more work is required to improved overall performance and scalability. / text

In this paper, the author presents his current research topic, objectives of research as well as research questions. The paper motivates the integration of implicit background knowledge in data mining and optimization techniques based on semantic web knowledge bases. Furthermore, it outlines work of related research areas and states the research methodology

AGUIA é uma aplicação web front-end, desenvolvida para gerenciar dados clínicos, demográficos e biomoleculares de pacientes coletados durante os ensaios clínicos gastrointestinais no MD Anderson Cancer Center. A diversidade de metodologias envolvidas na triagem de pacientes e no processamento da amostra traz uma heterogeneidade dos tipos de dados correspondentes. Sendo assim, estes devem ser baseados em uma arquitetura orientada a recurso que transforma dados heterogêneos em dados semânticos, mais especificamente em RDF (Resource Description Framework - Estrutura para a descrição de recursos). O banco de dados escolhido foi o S3DB, por este ter cumprido os requisitos necessários de transformação dos dados heterogêneos de diferentes fontes em RDF, distinguindo explicitamente a descrição do domínio e sua instanciação, permitindo simultaneamente a contínua edição de ambos. Além disso, ele usa um protocolo REST, e é de código aberto e domínio público o que facilita o desenvolvimento e divulgação. Contudo, por mais abrangente e flexível, um formato de web semântica pode por si só, não abordar a questão de representar o conteúdo de uma forma que faça sentido para especialistas do domínio. Assim, o objetivo do trabalho aqui descrito foi identificar um conjunto adicional de descritores que forneceu as especificações para a interface gráfica do usuário. Esse objetivo foi perseguido através da identificação de um formalismo que faz uso do esquema RDF para permitir a montagem automática de interfaces gráficas de uma forma significativa. Um modelo RDF generalizado foi, portanto, definido de tal forma que as mudanças nos descritores gráficos sejam automaticamente e imediatamente refletidas na configuração da aplicação web do cliente, que também está disponível neste trabalho. Embora os padrões de design identificados reflitam e beneficiem os requisitos específicos de interagir com os dados gerados pelos ensaios clínicos, a expectativa é que eles contenham pistas para uma solução de propósito geral. Em particular, sugere-se que os padrões mais úteis identificados pelos utilizadores deste sistema sejam suscetíveis de serem reutilizáveis para outras fontes de dados, ou pelo menos para outros bancos de dados semânticos de ensaios clínicos. / AGUIA is a web application front-end originally developed to manage clinical, demographic and biomolecular patient data collected during gastrointestinal clinical trials at MD Anderson Cancer Center. The diversity of methodologies involved in patient screening and sample processing, brings corresponding heterogeneity of data types. Thus, this data must be based on a Resource Oriented Architecture that transforms heterogeneous data in semantic data, most specifically in RDF (Resource Description Framework). The database chosen was a S3DB, because it met the necessary requirements of transforming heterogeneous data from different sources in RDF, explicitly distinguishing the description of the domain from its instantiation, while allowing for continuous editing of both. Furthermore, it uses a REST protocol, and is open source and in the public domain which facilitates development and dissemination. Nevertheless, comprehensive and flexible a semantic web format may be, it does not by itself address the issue of representing content in a form that makes sense for domain experts. Accordingly, the goal of the work described here was to identify an additional set of descriptors that provide specifications for the graphic user interface. That goal was pursued by identifying a formalism that makes use of the RDF schema to enable automatic assembly of graphic user interfaces in a meaningful manner. A generalized RDF model was therefore defined such that changes in the graphic descriptors are automatically and immediately reflected into the configuration of the client web browser interface application, which is also made available with this report. Although the design patterns identified reflect, and benefit, from the specific requirements of interacting with data generated by clinical trials, the expectation is that they contain clues for a general purpose solution. In particular, it is suggested that the most useful patterns identified by the users of this system are susceptible to being reusable for other data sources, or at least for other clinical trial semantic web data stores.

No description available.

Made available in DSpace on 2015-03-04T18:50:20Z (GMT). No. of bitstreams: 1 Dissertacao_MiriaSCC.pdf: 3267159 bytes, checksum: f201a630eab8fd18b0da112537958c44 (MD5) Previous issue date: 2010-03-04 / Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior / AGUIA is a web application front-end originally developed to manage clinical, demographic and biomolecular patient data collected during gastrointestinal clinical trials at MD Anderson Cancer Center. The diversity of methodologies involved in patient screening and sample processing, brings corresponding heterogeneity of data types. Thus, this data must be based on a Resource Oriented Architecture that transforms heterogeneous data in semantic data, most specifically in RDF (Resource Description Framework). The database chosen was a S3DB, because it met the necessary requirements of transforming heterogeneous data from different sources in RDF, explicitly distinguishing the description of the domain from its instantiation, while allowing for continuous editing of both. Furthermore, it uses a REST protocol, and is open source and in the public domain which facilitates development and dissemination. Nevertheless, comprehensive and flexible a semantic web format may be, it does not by itself address the issue of representing content in a form that makes sense for domain experts. Accordingly, the goal of the work described here was to identify an additional set of descriptors that provide specifications for the graphic user interface. That goal was pursued by identifying a formalism that makes use of the RDF schema to enable automatic assembly of graphic user interfaces in a meaningful manner. A generalized RDF model was therefore defined such that changes in the graphic descriptors are automatically and immediately reflected into the configuration of the client web browser interface application, which is also made available with this report. Although the design patterns identified reflect, and benefit, from the specific requirements of interacting with data generated by clinical trials, the expectation is that they contain clues for a general purpose solution. In particular, it is suggested that the most useful patterns identified by the users of this system are susceptible to being reusable for other data sources, or at least for other clinical trial semantic web data stores. / AGUIA é uma aplicação web front-end, desenvolvida para gerenciar dados clínicos, demográficos e biomoleculares de pacientes coletados durante os ensaios clínicos gastrointestinais no MD Anderson Cancer Center. A diversidade de metodologias envolvidas na triagem de pacientes e no processamento da amostra traz uma heterogeneidade dos tipos de dados correspondentes. Sendo assim, estes devem ser baseados em uma arquitetura orientada a recurso que transforma dados heterogêneos em dados semânticos, mais especificamente em RDF (Resource Description Framework - Estrutura para a descrição de recursos). O banco de dados escolhido foi o S3DB, por este ter cumprido os requisitos necessários de transformação dos dados heterogêneos de diferentes fontes em RDF, distinguindo explicitamente a descrição do domínio e sua instanciação, permitindo simultaneamente a contínua edição de ambos. Além disso, ele usa um protocolo REST, e é de código aberto e domínio público o que facilita o desenvolvimento e divulgação. Contudo, por mais abrangente e flexível, um formato de web semântica pode por si só, não abordar a questão de representar o conteúdo de uma forma que faça sentido para especialistas do domínio. Assim, o objetivo do trabalho aqui descrito foi identificar um conjunto adicional de descritores que forneceu as especificações para a interface gráfica do usuário. Esse objetivo foi perseguido através da identificação de um formalismo que faz uso do esquema RDF para permitir a montagem automática de interfaces gráficas de uma forma significativa. Um modelo RDF generalizado foi, portanto, definido de tal forma que as mudanças nos descritores gráficos sejam automaticamente e imediatamente refletidas na configuração da aplicação web do cliente, que também está disponível neste trabalho. Embora os padrões de design identificados reflitam e beneficiem os requisitos específicos de interagir com os dados gerados pelos ensaios clínicos, a expectativa é que eles contenham pistas para uma solução de propósito geral. Em particular, sugere-se que os padrões mais úteis identificados pelos utilizadores deste sistema sejam suscetíveis de serem reutilizáveis para outras fontes de dados, ou pelo menos para outros bancos de dados semânticos de ensaios clínicos.

Semantic interoperability within the health care sector requires that patient data be fully available and shared without ambiguity across participating health facilities. The need for the current research was based on federal stipulations that required health facilities provide complete and optimal care to patients by allowing full access to their health records. The ongoing discussions to achieve interoperability within the health care industry continue to emphasize the need for healthcare facilities to successfully adopt and implement Electronic Health Record (EHR) systems. Reluctance by the healthcare industry to implement these EHRs for the purpose of achieving interoperability has led to the current research problem where it was determined that there is no existing single data standardization structure that can effectively share and interpret patient data within heterogeneous systems. The current research used the design science research methodology (DSRM) to design and develop a master data standardization and translation (MDST) model that allowed seamless exchange of healthcare data among multiple facilities. To achieve interoperability through a common data standardization structure, where multiple independent data models can coexist, the translation mechanism incorporated the use of the Resource Description Framework (RDF). Using RDF, a universal exchange language, allowed for multiple data models and vocabularies to be easily combined and interrelated within a single environment thereby reducing data definition ambiguity. Based on the results from the research, key functional capabilities to effectively map and translate health data were documented. The research solution addressed two primary issues that impact semantic interoperability – the need for a centralized standards repository and a framework that effectively maps and translates data between various EHRs and vocabularies. Thus, health professionals have a single interpretation of health data across multiple facilities which ensures the integrity and validity of patient care. The research contributed to the field of design science development through the advancements of the underlying theories, phases, and frameworks used in the design and development of data translation models. While the current research focused on the development of a single, common information model, further research opportunities and recommendations could include investigations into the implementation of these types of artifacts within a single environment at a multi-facility hospital entity.