18,119 research outputs found

    A layered framework for pattern-based ontology evolution

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    The challenge of ontology-driven modelling of information components is well known in both academia and industry. In this paper, we present a novel approach to deal with customisation and abstraction of ontology-based model evolution. As a result of an empirical study, we identify a layered change operator framework based on the granularity, domain-speciïŹcity and abstraction of changes. The implementation of the operator framework is supported through layered change logs. Layered change logs capture the objective of ontology changes at a higher level of granularity and support a comprehensive understanding of ontology evolution. The layered change logs are formalised using a graph-based approach. We identify the recurrent ontology change patterns from an ontology change log for their reuse. The identiïŹed patterns facilitate optimizing and improving the deïŹnition of domain-speciïŹc change patterns

    Composite ontology change operators and their customizable evolution strategies

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    Change operators are the building blocks of ontology evolution. Elementary, composite and complex change operators have been suggested. While lower-level change operators are useful in terms of finegranular representation of ontology changes, representing the intent of change requires higher-level change operators. Here, we focus on higherlevel composite change operators to perform an aggregated task. We introduce composite-level evolution strategies. The central role of the evolution strategies is to preserve the intent of the composite change with respect to the user’s requirements and to reduce the change operational cost. Composite-level evolution strategies assist in avoiding the illegal changes or presence of illegal axioms that may generate inconsistencies during application of a composite change. We discuss few composite changes along with the defined evolution strategies as an example that allow users to control and customize the ontology evolution process

    Graph-based discovery of ontology change patterns

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    Ontologies can support a variety of purposes, ranging from capturing conceptual knowledge to the organisation of digital content and information. However, information systems are always subject to change and ontology change management can pose challenges. We investigate ontology change representation and discovery of change patterns. Ontology changes are formalised as graph-based change logs. We use attributed graphs, which are typed over a generic graph with node and edge attribution.We analyse ontology change logs, represented as graphs, and identify frequent change sequences. Such sequences are applied as a reference in order to discover reusable, often domain-specific and usagedriven change patterns. We describe the pattern discovery algorithms and measure their performance using experimental result

    State-of-the-art on evolution and reactivity

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    This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

    Empirical analysis of impacts of instance-driven changes in ontologies

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    Changes in the characterization of instances in digital contents are one of the rationales to change or evolve ontologies which support the domain. These changes can impacts on one or more of interrelated ontologies. Before implementing changes, their impact on the target ontology, other dependent ontologies or dependent systems should be analysed. We investigate three concerns for the determination of impacts of changes in ontologies: representation of changes to ensure minimum impact, impact determination and integrity determination. Key elements of our solution are the operationalization of change operations to minimize impacts, a parameterization approach for the determination of impacts, a categorization scheme for identified impacts, and prioritization technique for change operations based on the severity of impacts

    Quantum Ontologies and Mind-Matter Synthesis

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    Aspects of a quantum mechanical theory of a world containing efficacious mental aspects that are closely tied to brains, but that are not identical to brains.Comment: 69 pages. Invited contribution to Xth Max Born Symposium: "Quantum Future". Published in "Quantum Future", eds. P. Blanchard and A. Jadczyk, Springer-Verlag, 1999, ISBN 3-540-65218-3. LBNL 4072

    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

    Ontology-based modelling of architectural styles

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    The conceptual modelling of software architectures is of central importance for the quality of a software system. A rich modelling language is required to integrate the different aspects of architecture modelling, such as architectural styles, structural and behavioural modelling, into a coherent framework. Architectural styles are often neglected in software architectures. We propose an ontological approach for architectural style modelling based on description logic as an abstract, meta-level modelling instrument. We introduce a framework for style definition and style combination. The application of the ontological framework in the form of an integration into existing architectural description notations is illustrated

    Ontology-based composition and matching for dynamic cloud service coordination

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    Recent cross-organisational software service offerings, such as cloud computing, create higher integration needs. In particular, services are combined through brokers and mediators, solutions to allow individual services to collaborate and their interaction to be coordinated are required. The need to address dynamic management - caused by cloud and on-demand environments - can be addressed through service coordination based on ontology-based composition and matching techniques. Our solution to composition and matching utilises a service coordination space that acts as a passive infrastructure for collaboration where users submit requests that are then selected and taken on by providers. We discuss the information models and the coordination principles of such a collaboration environment in terms of an ontology and its underlying description logics. We provide ontology-based solutions for structural composition of descriptions and matching between requested and provided services
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