Ontology acquisition and exchange of evolutionary product-brokering agents

Agent-based electronic commerce (e-commerce) has been booming with the development of the Internet and agent technologies. However, little effort has been devoted to exploring the learning and evolving capabilities of software agents. This paper addresses issues of evolving software agents in e-commerce applications. An agent structure with evolution features is proposed with a focus on internal hierarchical knowledge. We argue that knowledge base of agents should be the cornerstone for their evolution capabilities, and agents can enhance their knowledge bases by exchanging knowledge with other agents. In this paper, product ontology is chosen as an instance of knowledge base. We propose a new approach to facilitate ontology exchange among e-commerce agents. The ontology exchange model and its formalities are elaborated. Product-brokering agents have been designed and implemented, which accomplish the ontology exchange process from request to integration

Ontology-based domain modelling for consistent content change management

Ontology-based modelling of multi-formatted software application content is a challenging area in content management. When the number of software content unit is huge and in continuous process of change, content change management is important. The management of content in this context requires targeted access and manipulation methods. We present a novel approach to deal with model-driven content-centric information systems and access to their content. At the core of our approach is an ontology-based semantic annotation technique for diversely formatted content that can improve the accuracy of access and systems evolution. Domain ontologies represent domain-specific concepts and conform to metamodels. Different ontologies - from application domain ontologies to software ontologies - capture and model the different properties and perspectives on a software content unit. Interdependencies between domain ontologies, the artifacts and the content are captured through a trace model. The annotation traces are formalised and a graph-based system is selected for the representation of the annotation traces

Ontological support for the evolution of future services oriented architectures

Services Oriented Architectures (SOA) have emerged as a useful framework for developing interoperable, large-scale systems, typically implemented using the Web Services (WS) standards. However, the maintenance and evolution of SOA systems present many challenges. SmartLife applications are intelligent user-centered systems and a special class of SOA systems that present even greater challenges for a software maintainer. Ontologies and ontological modeling can be used to support the evolution of SOA systems. This paper describes the development of a SOA evolution ontology and its use to develop an ontological model of a SOA system. The ontology is based on a standard SOA ontology. The ontological model can be used to provide semantic and visual support for software maintainers during routine maintenance tasks. We discuss a case study to illustrate this approach, as well as the strengths and limitations

Multi-site software engineering ontology instantiations management using reputation based decision making

In this paper we explore the development of systems for software engineering ontology instantiations management in the methodology for multi-site distributed software development. Ultimately the systems facilitate collaboration of teams in multi-site distributed software development. In multi-site distributed environment, team members in the software engineering projects have naturally an interaction with each other and share lots of project data/agreement amongst themselves. Since theyare not always residing at the same place and face-to-face meetings hardly happen, there is a need for methodology and tools that facilitate effective communication for efficient collaboration. Whist multi-site distributed teams collaborate, there are a lot of shared project data updated or created. In a large volume of project data, systematic management is of importance. Software engineering knowledge is represented in the software engineering ontology whose instantiations, which are undergoing evolution, need a good management system. Software engineering ontology instantiations signify project information which is shared and has evolved to reflect project development, changes in the software requirements or in the design process, to incorporate additional functionality to systems or to allow incremental improvement, etc

Multi-représentation d'une ontologie : OWL, bases de données, systèmes de types et d'objets.

ISBN: 978-1-60558-842-1International audienceDue to the emergence of the semantic Web and the increasing need to formalize human knowledge, ontologie engineering is now an important activity. But is this activity very different from other ones like software engineering, for example ? In this paper, we investigate analogies between ontologies on one hand, types, objects and data bases on the other one, taking into account the notion of evolution of an ontology. We represent a unique ontology using different paradigms, and observe that the distance between these different concepts is small. We deduce from this constatation that ontologies and more specifically ontology description languages can take advantage of beeing fertilizated with some other computer science domains and inherit important characteristics as modularity, for example

Analyzing evolution of variability in a software product line: from contexts and requirements to features

In the long run, features of a software product line (SPL) evolve with respect to changes in stakeholder requirements and system contexts. Neither domain engineering nor requirements engineering handles such co-evolution of requirements and contexts explicitly, making it especially hard to reason about the impact of co-changes in complex scenarios. In this paper, we propose a problem-oriented and value-based analysis method for variability evolution analysis. The method takes into account both kinds of changes (requirements and contexts) during the life of an evolving software product line. The proposed method extends the core requirements engineering ontology with the notions to represent variability-intensive problem decomposition and evolution. On the basis of problem-orientation, the analysis method identifies candidate changes, detects influenced features, and evaluates their contributions to the value of the SPL. The process of applying the analysis method is illustrated using a concrete case study of an evolving enterprise software system, which has confirmed that tracing back to requirements and contextual changes is an effective way to understand the evolution of variability in the software product line

ChImp:Visualizing Ontology Changes and their Impact in Protégé

Today, ontologies are an established part of many applications and research. However, ontologies evolve over time, and ontology editors---engineers and domain experts---need to be aware of the consequences of changes while editing. Ontology editors might not be fully aware of how they are influencing consistency, quality, or the structure of the ontology, possibly causing applications to fail. To support editors and increase their sensitivity towards the consequences of their actions, we conducted a user survey to elicit preferences for representing changes, e.g., with ontology metrics such as number of classes and properties. Based on the survey, we developed ChImp---a Protégé plug-in to display information about the impact of changes in real-time. During editing of the ontology, ChImp lists the applied changes, checks and displays the consistency status, and reports measures describing the effect on the structure of the ontology. Akin to software IDEs and integrated testing approaches, we hope that displaying such metrics will help to improve ontology evolution processes in the long run

Interoperability and the Need for Intelligent Software: A Historical Perspective

With the objective of defining the interoperability theme of this year’s conference it is the purpose of this paper1 to trace the evolution of intelligent software from data-centric applications that essentially encapsulate their data environment to ontology-based applications with automated reasoning capabilities. The author draws a distinction between human intelligence and component capabilities within a more general definition of intelligence; - a kind of intelligence that can be embedded in computer software. The primary vehicle in the quest for intelligent software has been the gradual recognition of the central role played by data and information, rather than the logic and functionality of the application. The three milestones in this evolution have been: the separation of data management from the internal domain of the application; the development of standard data exchange protocols such as XML that allow machine interpretable structure and meaning to be added to data exchange packages; and, the ability to build information models that are rich in relationships and are thereby capable of supporting the automated reasoning capabilities of software agents. The author suggests that the vision of a Semantic Web environment in which ontology-based Web services with intelligent capabilities are able to discover each other and individually or in self-configured groups perform useful tasks, is not only feasible but imminently realizable. The capabilities of an experimental proof-of-concept system featuring semantic Web services that was demonstrated during the 2002 meeting of this annual conference series is described in summary form

Graph-based discovery of ontology change patterns

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