Integration-oriented ontology

The purpose of an integration-oriented ontology is to provide a conceptualization of a domain of interest for automating the data integration of an evolving and heterogeneous set of sources using Semantic Web technologies. It links domain concepts to each of the underlying data sources via schema mappings. Data analysts, who are domain experts but not necessarily have technical data management skills, pose ontology-mediated queries over the conceptualization, which are automatically translated to the appropriate query language for the sources at hand. Following well-established rules when designing schema mappings allows to automate the process of query rewriting and execution.Postprint (author's final draft

An ontology of agile aspect oriented software development

Both agile methods and aspect oriented programming (AOP) have emerged in recent years as new paradigms in software development. Both promise to free the process of building software systems from some of the constraints of more traditional approaches. As a software engineering approach on the one hand, and a software development tool on the other, there is the potential for them to be used in conjunction. However, thus far, there has been little interplay between the two. Nevertheless, there is some evidence that there may be untapped synergies that may be exploited, if the appropriate approach is taken to integrating AOP with agile methods. This paper takes an ontological approach to supporting this integration, proposing ontology enabled development based on an analysis of existing ontologies of aspect oriented programming, a proposed ontology of agile methods, and a derived ontology of agile aspect oriented development

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

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

Greeks and Trojans Together

This paper describes a comprehensive solution for the integration of object oriented ontology representation frameworks with logic-based agent communication frameworks. The proposed solution addresses the problem at both the agent communication level and the agent implementation level. At the agent communication level, we propose to extend logic content languages with some domain independent operators that allow building logic constructs as propositions from domain dependent entities defined in an object oriented ontology. At the implementation level, we propose to use object-oriented databases as the support for the agent information. Finally, we propose an automatic mechanism for translating agent messages using the extended content language into ODMG OQL commands, which are then used to interact with the object-oriented database. This binding mechanism relies on a special purpose data dictionary representing the mapping between the domain ontology and the agent internal database

A Semantic Web Approach to Heterogeneous Metadata Integration

[[abstract]]Heterogeneous metadata integration is an issue in digital libraries. Mapping is often used for an integrated metadata access, but the implicit knowledge and relations embedded in metadata are ignored. This paper aims to present a semantic web approach to heterogeneous metadata integration of biodiversity repositories. First, implicit knowledge and relations in metadata are extracted out and transformed into a shared ontology with expression of RDF and OWL languages. Next the shared ontology plays an inter-lingua role in harmonizing heterogeneous metadata to achieve an ontology mapping with a unified view. Then the shared ontology is expressed by SWRL for inference query to offer in-depth semantic discovery. Finally four question answering oriented queries are employed to examine the feasibility of the shared ontology for heterogeneous metadata integration.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙

AOSD Ontology 1.0 - Public Ontology of Aspect-Orientation

This report presents a Common Foundation for Aspect-Oriented Software Development. A Common Foundation is required to enable effective communication and to enable integration of activities within the Network of Excellence. This Common Foundation is realized by developing an ontology, i.e. the shared meaning of terms and concepts in the domain of AOSD. In the first part of this report, we describe the definitions of an initial set of common AOSD terms. There is general agreement on these definitions. In the second part, we describe the Common Foundation task in detail

Ontology-oriented e-government service integration utilising the semantic web

University of Technology, Sydney. Faculty of Engineering and Information Technology.E-government service integration process has recently become an important research topic in e-government domain since many countries have developed various levels of e-government services. Non-interoperability between government agencies in service delivery implementation and platform posing the technical challenge, and the lack of the formulated modelling framework is the main methodological obstacle on the way of achieving dynamic delivery of integrated e-government services. This research is a study of the problems associated with the integration and delivery of integrated e-government services, and proposes a novel solution to tackle them. We start with investigating the fundamentals of e-government as a field of research to build a sensible argument for the questions investigated by this research, which lead to the exposure of the methodological as well as technological problems with the mechanics of e-government in the areas of service integration and delivery. The outcomes of this study in Chapters 3, 4, 5, 6, and 7 respectively 1) suggests the most practically relevant and technically possible evolutionary pathway to e-government transformation, 2) proposes a modified software engineering process to achieve such transformation, 3) develops an innovative framework for modelling the service integration, 4) proposes an ontology as its knowledgebase, and 5) develops an innovative and intelligent software to support the practice of service integration and delivery. These outcomes collectively result in the introduction of a novel, complete and coherent solution for the abovementioned problems. This research is a cross disciplinary study of software integration engineering frameworks, e-government service delivery platform and semantic web technology, all working to devise the most efficient and robust framework of using semantic web capabilities to enable the delivery of integrated e-government services in an intelligent platform

Methods and techniques for generation and integration of Web ontology data

University of Technology, Sydney. Faculty of Information Technology.Data integration over the web or across organizations encounters several unfavorable features: heterogeneity, decentralization, incompleteness, and uncertainty, which prevent information from being fully utilized for advanced applications such as decision support services. The basic idea of ontology related approaches for data integration is to use one or more ontology schemas to interpret data from different sources. Several issues will come up when actually implementing the idea: (1) How to develop the domain ontology schema(s) used for the integration; (2) How to generate ontology data for domain ontology schema if the data are not in the right format and to create and manage ontology data in an appropriate way; (3) How to improve the quality of integrated ontology data by reducing duplications and increasing completeness and certainty. This thesis focuses on the above issues and develops a set of methods to tackle them. First, a key information mining method is developed to facilitate the development of interested domain ontology schemas. It effectively extracts from the web sites useful terms and identifies taxonomy information which is essential to ontology schema construction. A prototype system is developed to use this method to help create domain ontology schemas. Second, this study develops two complemented methods which are light weighted and more semantic web oriented to address the issue of ontology data generation. One method allows users to convert existing structured data (mostly XML data) to ontology data; another enables users to create new ontology data directly with ease.In addition, a web-based system is developed to allow users to manage the ontology data collaboratively and with customizable security constraints. Third, this study also proposes two methods to perform ontology data matching for the improvement of ontology data quality when an integration happens. One method uses the clustering approach. It makes use of the relational nature of the ontology data and captures different situations of matching, therefore resulting in an improvement of performance compared with the traditional canopy clustering method. The other method goes further by using a learning mechanism to make the matching more adaptive. New features are developed for training matching classifier by exploring particular characteristics of ontology data. This method also achieves better performance than those with only ordinary features. These matching methods can be used to improve data quality in a peer-to-peer framework which is proposed to integrate available ontology data from different peers

Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation