58,867 research outputs found

    Multi-Paradigm Reasoning for Access to Heterogeneous GIS

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    Accessing and querying geographical data in a uniform way has become easier in recent years. Emerging standards like WFS turn the web into a geospatial web services enabled place. Mediation architectures like VirGIS overcome syntactical and semantical heterogeneity between several distributed sources. On mobile devices, however, this kind of solution is not suitable, due to limitations, mostly regarding bandwidth, computation power, and available storage space. The aim of this paper is to present a solution for providing powerful reasoning mechanisms accessible from mobile applications and involving data from several heterogeneous sources. By adapting contents to time and location, mobile web information systems can not only increase the value and suitability of the service itself, but can substantially reduce the amount of data delivered to users. Because many problems pertain to infrastructures and transportation in general and to way finding in particular, one cornerstone of the architecture is higher level reasoning on graph networks with the Multi-Paradigm Location Language MPLL. A mediation architecture is used as a “graph provider” in order to transfer the load of computation to the best suited component – graph construction and transformation for example being heavy on resources. Reasoning in general can be conducted either near the “source” or near the end user, depending on the specific use case. The concepts underlying the proposal described in this paper are illustrated by a typical and concrete scenario for web applications

    ENHANCED BI SYSTEMS WITH ON-DEMAND DATA BASED ON SEMANTIC-ENABLED ENTERPRISE SOA

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    Since the 1990s, companies have been investing into IT infrastructure initiatives such as Enterprise Resource Planning (ERP) systems, Supply Chain Management (SCM) systems, and Customer Relationship Management (CRM) systems in order to increase efficiency, effectiveness, and internal process integration, among other goals. The current value of Business Intelligence (BI) for companies could be summarized by two main achievements: improvement of management of processes and improvement of operational processes. This paper will identify current requirements of BI and present a linkage to service-oriented architectures including added-values. Semantic-enabled Enterprise Service-Oriented Architecture (SESOA) is an enterprise solution that links businesses to external systems based on Web Services and SOA concept. It represents a lightweight web application that annotates Web Services that are coming from different service providers with semantics so that the indexing and discovery of these services can be more comprehensive. BI applications can be considered as service consumers in SESOA and can discover, select and invoke the services supplied by the external systems (service providers). In this way, SESOA forms the bridge between SOA and BI concepts to deliver in real time the ?on-demand? data as services and this opens the BI market to include SMEs as main resources of these services

    Ontology-based patterns for the integration of business processes and enterprise application architectures

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    Increasingly, enterprises are using Service-Oriented Architecture (SOA) as an approach to Enterprise Application Integration (EAI). SOA has the potential to bridge the gap between business and technology and to improve the reuse of existing applications and the interoperability with new ones. In addition to service architecture descriptions, architecture abstractions like patterns and styles capture design knowledge and allow the reuse of successfully applied designs, thus improving the quality of software. Knowledge gained from integration projects can be captured to build a repository of semantically enriched, experience-based solutions. Business patterns identify the interaction and structure between users, business processes, and data. Specific integration and composition patterns at a more technical level address enterprise application integration and capture reliable architecture solutions. We use an ontology-based approach to capture architecture and process patterns. Ontology techniques for pattern definition, extension and composition are developed and their applicability in business process-driven application integration is demonstrated

    Content-driven design and architecture of E-learning applications

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    E-learning applications combine content with learning technology systems to support the creation of content and its delivery to the learner. In the future, we can expect the distinction between learning content and its supporting infrastructure to become blurred. Content objects will interact with infrastructure services as independent objects. Our solution to the development of e-learning applications – content-driven design and architecture – is based on content-centric ontological modelling and development of architectures. Knowledge and modelling will play an important role in the development of content and architectures. Our approach integrates content with interaction (in technical and educational terms) and services (the principle organization for a system architecture), based on techniques from different fields, including software engineering, learning design, and knowledge engineering

    Model Based Development of Quality-Aware Software Services

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    Modelling languages and development frameworks give support for functional and structural description of software architectures. But quality-aware applications require languages which allow expressing QoS as a first-class concept during architecture design and service composition, and to extend existing tools and infrastructures adding support for modelling, evaluating, managing and monitoring QoS aspects. In addition to its functional behaviour and internal structure, the developer of each service must consider the fulfilment of its quality requirements. If the service is flexible, the output quality depends both on input quality and available resources (e.g., amounts of CPU execution time and memory). From the software engineering point of view, modelling of quality-aware requirements and architectures require modelling support for the description of quality concepts, support for the analysis of quality properties (e.g. model checking and consistencies of quality constraints, assembly of quality), tool support for the transition from quality requirements to quality-aware architectures, and from quality-aware architecture to service run-time infrastructures. Quality management in run-time service infrastructures must give support for handling quality concepts dynamically. QoS-aware modeling frameworks and QoS-aware runtime management infrastructures require a common evolution to get their integration

    Quality-aware model-driven service engineering

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    Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services

    Knowledge infrastructures for software service architectures

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    Software development has become a distributed, collaborative process based on the assembly of off-the-shelf and purpose-built components or services. The selection of software services from service repositories and their integration into software system architectures, but also the development of services for these repositories requires an accessible information infrastructure that allows the description and comparison of these services. General knowledge relating to software development is equally important in this context as knowledge concerning the application domain of the software. Both form two pillars on which the structural and behavioural properties of software services can be addressed. We investigate how this information space for software services can be organized. Focal point are ontologies that, in addition to the usual static view on knowledge, also intrinsically addresses the dynamics, i.e. the behaviour of software. We relate our discussion to the Web context, looking at the Web Services Framework and the Semantic Web as the knowledge representation framework
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