Designing websites with eXtensible web (xWeb) methodology

Today, eXtensible Markup Language (XML) is fast emerging as the dominant standard for storing, describing, representing and interchanging data among various enterprises systems and databases in the context of complex web enterprises information systems (EIS). Conversely, for web EIS (such as e-commerce and portals) to be successful, it is important to apply a high level, model driven solutions and meta-data vocabularies to design and implementation techniques that are capable of handling heterogonous schemas and documents. For this, we need a methodology that provides a higher level of abstraction of the domain in question with rigorously defined standards that are to be more widely understood by all stakeholders of the system. To-date, UML has proven itself as the language of choice for modeling EIS using OO techniques. With the introduction of XML Schema, which provides rich facilities for constraining and defining enterprise XML content, the combination of UML and XML technologies provide a good platform (and the flexibility) for modeling, designing and representing complex enterprise contents for building successful EIS. In this paper, we show how a layered view model coupled with a proven user interface analysis framework (WUiAM) is utilized in providing architectural construct and abstract website model (called eXtensible Web, xWeb), to model, design and implement simple, user-centred, collaborative websites at varying levels of abstraction. The uniqueness xWeb is that the model data (web user interface definitions, website data descriptions and constraints) and the web content are captured and represented at the conceptual level using views (one model) and can be deployed (multiple platform specific models) using one or more implementation models

A Business User Model-Driven Engineering Method for Developing Information Systems

This thesis is all about raising the level of abstraction at which information systems are built, using business end-users knowledge and MDE to achieve the result. The work intro- duces, first, Micro-Modelling Language (μML), a lightweight modelling language that is used to express basic structural and behavioural aspects of information systems using effectivily business-users knowledge of their desired system. Throughout the work, graphical notation and semantics for the language concepts are identified, providing a simpler and semantically cleaned modelling language than standard UML and other UML-based languages. The work also proposes BUILD (Business-User Information-Led Development), an End- User MDE approach to support the construction of information systems using high-level specifications and accelerate the development process using layered model transformation and code generation. Throughout the thesis, a number of development phases and model transformation steps are identified to allow the low-level technical detail be introduced and developed automatically by rules, with less end-users engagement. Domain-Specific code generators, for generating executable Java Swing Applications code and MySQL script, are used to demonstrate the validity of the research

Using Ontologies to Improve Answer Quality in Databases

One of the known shortcomings of relational and XML databases is that they overlook the semantics of terms when answering queries. Ontologies constitute a useful tool to convey the semantics of terms in databases. However, the problem of effectively using semantic information from ontologies is challenging. We first address this problem for relational databases by the notion of an ontology extended relation (OER). An OER contains an ordinary relation as well as an associated ontology that conveys semantic meaning about the terms being used. We then extend the relational algebra to query OERs. We build a prototype for the OER model and show that the system scales to handle large datasets. We then propose the concept of a similarity enhanced ontology (SEO), which brings a notion of similarity to a graph ontology. We extend TAX, one of the best known algebras for XML databases, with SEOs. The result is our TOSS system that provides a much higher answer quality than TAX does alone. We experimentally evaluate the TOSS system on the DBLP and SIGMOD bibliographic databases and show that TOSS has acceptable performance. These two projects have involved ontology integration for supporting semantic queries across heterogeneous databases. We show how to efficiently compute the canonical witness to the integrability of graph ontologies given a set of interoperation constraints. We have also developed a polynomial algorithm to compute a minimal witness to the integrability of RDF ontologies under a set of Horn clauses and negative constraints, and experimentally show that our algorithm works very well on real-life ontologies and scales to massive ontologies. We finally present our work on ontology-based similarity measures for finding relationships between ontologies and searching similar objects. These measures are applicable to practical classification systems, where ontologies can be DAG-structured, objects can be labeled with multiple terms, and ambiguity can be introduced by an evolving ontology or classifiers with imperfect knowledge. The experiments on a bioinformatics application show that our measures outperformed previous approaches

Implementation of Web Query Languages Reconsidered

Visions of the next generation Web such as the "Semantic Web" or the "Web 2.0" have triggered the emergence of a multitude of data formats. These formats have different characteristics as far as the shape of data is concerned (for example tree- vs. graph-shaped). They are accompanied by a puzzlingly large number of query languages each limited to one data format. Thus, a key feature of the Web, namely to make it possible to access anything published by anyone, is compromised. This thesis is devoted to versatile query languages capable of accessing data in a variety of Web formats. The issue is addressed from three angles: language design, common, yet uniform semantics, and common, yet uniform evaluation. % Thus it is divided in three parts: First, we consider the query language Xcerpt as an example of the advocated class of versatile Web query languages. Using this concrete exemplar allows us to clarify and discuss the vision of versatility in detail. Second, a number of query languages, XPath, XQuery, SPARQL, and Xcerpt, are translated into a common intermediary language, CIQLog. This language has a purely logical semantics, which makes it easily amenable to optimizations. As a side effect, this provides the, to the best of our knowledge, first logical semantics for XQuery and SPARQL. It is a very useful tool for understanding the commonalities and differences of the considered languages. Third, the intermediate logical language is translated into a query algebra, CIQCAG. The core feature of CIQCAG is that it scales from tree- to graph-shaped data and queries without efficiency losses when tree-data and -queries are considered: it is shown that, in these cases, optimal complexities are achieved. CIQCAG is also shown to evaluate each of the aforementioned query languages with a complexity at least as good as the best known evaluation methods so far. For example, navigational XPath is evaluated with space complexity O(q d) and time complexity O(q n) where q is the query size, n the data size, and d the depth of the (tree-shaped) data. CIQCAG is further shown to provide linear time and space evaluation of tree-shaped queries for a larger class of graph-shaped data than any method previously proposed. This larger class of graph-shaped data, called continuous-image graphs, short CIGs, is introduced for the first time in this thesis. A (directed) graph is a CIG if its nodes can be totally ordered in such a manner that, for this order, the children of any node form a continuous interval. CIQCAG achieves these properties by employing a novel data structure, called sequence map, that allows an efficient evaluation of tree-shaped queries, or of tree-shaped cores of graph-shaped queries on any graph-shaped data. While being ideally suited to trees and CIGs, the data structure gracefully degrades to unrestricted graphs. It yields a remarkably efficient evaluation on graph-shaped data that only a few edges prevent from being trees or CIGs

Strategies for Managing Linked Enterprise Data

Data, information and knowledge become key assets of our 21st century economy. As a result, data and knowledge management become key tasks with regard to sustainable development and business success. Often, knowledge is not explicitly represented residing in the minds of people or scattered among a variety of data sources. Knowledge is inherently associated with semantics that conveys its meaning to a human or machine agent. The Linked Data concept facilitates the semantic integration of heterogeneous data sources. However, we still lack an effective knowledge integration strategy applicable to enterprise scenarios, which balances between large amounts of data stored in legacy information systems and data lakes as well as tailored domain specific ontologies that formally describe real-world concepts. In this thesis we investigate strategies for managing linked enterprise data analyzing how actionable knowledge can be derived from enterprise data leveraging knowledge graphs. Actionable knowledge provides valuable insights, supports decision makers with clear interpretable arguments, and keeps its inference processes explainable. The benefits of employing actionable knowledge and its coherent management strategy span from a holistic semantic representation layer of enterprise data, i.e., representing numerous data sources as one, consistent, and integrated knowledge source, to unified interaction mechanisms with other systems that are able to effectively and efficiently leverage such an actionable knowledge. Several challenges have to be addressed on different conceptual levels pursuing this goal, i.e., means for representing knowledge, semantic data integration of raw data sources and subsequent knowledge extraction, communication interfaces, and implementation. In order to tackle those challenges we present the concept of Enterprise Knowledge Graphs (EKGs), describe their characteristics and advantages compared to existing approaches. We study each challenge with regard to using EKGs and demonstrate their efficiency. In particular, EKGs are able to reduce the semantic data integration effort when processing large-scale heterogeneous datasets. Then, having built a consistent logical integration layer with heterogeneity behind the scenes, EKGs unify query processing and enable effective communication interfaces for other enterprise systems. The achieved results allow us to conclude that strategies for managing linked enterprise data based on EKGs exhibit reasonable performance, comply with enterprise requirements, and ensure integrated data and knowledge management throughout its life cycle

3rd EGEE User Forum

We have organized this book in a sequence of chapters, each chapter associated with an application or technical theme introduced by an overview of the contents, and a summary of the main conclusions coming from the Forum for the chapter topic. The first chapter gathers all the plenary session keynote addresses, and following this there is a sequence of chapters covering the application flavoured sessions. These are followed by chapters with the flavour of Computer Science and Grid Technology. The final chapter covers the important number of practical demonstrations and posters exhibited at the Forum. Much of the work presented has a direct link to specific areas of Science, and so we have created a Science Index, presented below. In addition, at the end of this book, we provide a complete list of the institutes and countries involved in the User Forum

Análisis Hibernate como Tecnología de Persistencia de Objetos sobre Base de Datos Realcionales en Aplicaciones Empresariales: Caso Práctico: Control de Bienes del Gobierno Municipal de Carlos Julio Arosemena Tola

Se analizó la tecnología Hibernate como Framework de persistencia en el desarrollo de aplicaciones web. Caso Práctico: Control y gestión de bienes del Gobierno Autónomo Descentralizo Municipal del cantón Arosemena Tola, Provincia Napo. Para el desarrollo de esta investigación se utilizó el método de investigación Científico con el fin de levantar, recopilar información, analizar e interpretar los resultados que permitieron la comprobación de la hipótesis para ello se utilizaron recursos hardware, software para la implementación del sistema y ofimático como son las encuestas para su posterior tabulación y aplicación del método estadístico T-Student; además se hizo uso del método descriptivo para describir las características más sobresalientes de la tecnología Hibernate. Como resultados del análisis y comparación de las tecnologías de Mapeo Objeto Relacional (ORM) Hibernate y EclipseLink, se mostro que Hibernate alcanzo el 98% de eficiencia frente a 78,43% alcanzado por EclipseLink. Como se demostró en el estudio que la tecnología Hibernate es de gran ayuda para los desarrolladores de aplicaciones basados en la tecnología J2EE. Se concluye que reduce significativamente el tiempo de desarrollo de la aplicación, consume menos recursos, permite adaptar código de acuerdo a la necesidad del usuario, puede integrarse con una gran variedad de Frameworks, posee una excelente documentación y se acopla muy bien a la arquitectura Modelo Vista Controlador. Se recomienda el uso de este Framework para el desarrollo de aplicaciones web empresariales puesto que ofrece grandes ventajas al reducir tiempo de desarrollo, eliminando muchos problemas con el manejo de base de datos relacionales

Banco de dados biológico no modelo relacional para mineração de dados em genomas completos de procariotos disponibilizados pelo NCBI GenBank

Resumo: O NCBI GenBank, um dos três principais bancos de dados primários, tem centralizado as informações obtidas pelos processos de sequenciamento de DNA e/ou RNA e as tem distribuído no formato de arquivos textos. Nos servidores de arquivos do GenBank, para o Domínio Bactéria e Domínio Archea, existe um arquivo em formato específico para cada organismo, cromossomo ou plasmídeo completamente sequenciado, com seus genomas e respectivas anotações. Detectou-se a ausência de um modelo de banco de dados para armazenar todas as informações, bem como se observou a necessidade de redistribuir essas informações no formato de banco de dados relacional. Este trabalho propõe um modelo de banco de dados relacional e um conjunto de ferramentas para análise, transposição dos dados no formato texto para o modelo de banco de dados relacional desenvolvido e estratégias de atualização. O modelo foi desenvolvido a partir da análise da especificação do GenBank e da observação das informações de organismos espalhados em mais de 2000 arquivos. Para o desenvolvimento das ferramentas, adotou-se a metodologia da prototipação, padrões de projetos, testes e análises de desempenho. Os resultados obtidos demonstram a possibilidade de armazenar todos os dados nos principais SGBD, com redução significativa da redundância nos dados e obtenção de alto desempenho nas quatro etapas do processo: 1) sincronização dos arquivos de texto em um repositório local a partir do servidor de arquivos do NCBI; 2) análise dos arquivos e interpretação dos campos; 3) carga dos dados analisados no banco de dados e; 4) aderência do modelo desenvolvido com a especificação e desempenho observado nas consultas feitas. Esta dissertação contribui para um novo modelo de organização, acesso e distribuição das informações do NCBI GenBank