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

A Query Integrator and Manager for the Query Web

We introduce two concepts: the Query Web as a layer of interconnected queries over the document web and the semantic web, and a Query Web Integrator and Manager (QI) that enables the Query Web to evolve. QI permits users to write, save and reuse queries over any web accessible source, including other queries saved in other installations of QI. The saved queries may be in any language (e.g. SPARQL, XQuery); the only condition for interconnection is that the queries return their results in some form of XML. This condition allows queries to chain off each other, and to be written in whatever language is appropriate for the task. We illustrate the potential use of QI for several biomedical use cases, including ontology view generation using a combination of graph-based and logical approaches, value set generation for clinical data management, image annotation using terminology obtained from an ontology web service, ontology-driven brain imaging data integration, small-scale clinical data integration, and wider-scale clinical data integration. Such use cases illustrate the current range of applications of QI and lead us to speculate about the potential evolution from smaller groups of interconnected queries into a larger query network that layers over the document and semantic web. The resulting Query Web could greatly aid researchers and others who now have to manually navigate through multiple information sources in order to answer specific questions

An open standard for the exchange of information in the Australian timber sector

The purpose of this paper is to describe business-to-business (B2B) communication and the characteristics of an open standard for electronic communication within the Australian timber and wood products industry. Current issues, future goals and strategies for using business-to-business communication will be considered. From the perspective of the Timber industry sector, this study is important because supply chain efficiency is a key component in an organisation's strategy to gain a competitive advantage in the marketplace. Strong improvement in supply chain performance is possible with improved business-to-business communication which is used both for building trust and providing real time marketing data. Traditional methods such as electronic data interchange (EDI) used to facilitate B2B communication have a number of disadvantages, such as high implementation and running costs and a rigid and inflexible messaging standard. Information and communications technologies (ICT) have supported the emergence of web-based EDI which maintains the advantages of the traditional paradigm while negating the disadvantages. This has been further extended by the advent of the Semantic web which rests on the fundamental idea that web resources should be annotated with semantic markup that captures information about their meaning and facilitates meaningful machine-to-machine communication. This paper provides an ontology using OWL (Web Ontology Language) for the Australian Timber sector that can be used in conjunction with semantic web services to provide effective and cheap B2B communications

The Semantic Automated Discovery and Integration (SADI) Web service Design-Pattern, API and Reference Implementation

Background. 
The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community.

Description. 
SADI – Semantic Automated Discovery and Integration – is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services “stack”, SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers.

Conclusions.
SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behavior we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services can be explored in a manner very similar to data housed in static triple-stores, thus facilitating the intersection of Web services and Semantic Web technologies

A Shared Ontology Approach to Semantic Representation of BIM Data

Architecture, engineering, construction and facility management (AEC-FM) projects involve a large number of participants that must exchange information and combine their knowledge for successful completion of a project. Currently, most of the AEC-FM domains store their information about a project in text documents or use XML, relational, or object-oriented formats that make information integration difficult. The AEC-FM industry is not taking advantage of the full potential of the Semantic Web for streamlining sharing, connecting, and combining information from different domains. The Semantic Web is designed to solve the information integration problem by creating a web of structured and connected data that can be processed by machines. It allows combining information from different sources with different underlying schemas distributed over the Internet. In the Semantic Web, all data instances and data schema are stored in a graph data store, which makes it easy to merge data from different sources. This paper presents a shared ontology approach to semantic representation of building information. The semantic representation of building information facilitates finding and integrating building information distributed in several knowledge bases. A case study demonstrates the development of a semantic based building design knowledge base

Business integration models in the context of web services.

E-commerce development and applications have been bringing the Internet to business and marketing and reforming our current business styles and processes. The rapid development of the Web, in particular, the introduction of the semantic web and web service technologies, enables business processes, modeling and management to enter an entirely new stage. Traditional web based business data and transactions can now be analyzed, extracted and modeled to discover new business rules and to form new business strategies, let alone mining the business data in order to classify customers or products. In this paper, we investigate and analyze the business integration models in the context of web services using a micro-payment system because a micro-payment system is considered to be a service intensive activity, where many payment tasks involve different forms of services, such as payment method selection for buyers, security support software, product price comparison, etc. We will use the micro-payment case to discuss and illustrate how the web services approaches support and transform the business process and integration model.