Ontological Engineering in Pervasive Computing Environments

Pervasive computing is a broad and compelling research topic in computer science that focuses on the applications of technology to assist users in everyday life situations. It seeks to provide proactive and self-tuning environments and devices to seamlessly augment a person’s knowledge and decision making ability, while requiring as little direct user interaction as possible. Its vision is the creation of an environment saturated with seamlessly integrated devices with computing and communication capabilities. The realisation of this vision requires that a very large number of devices and software components interoperate seamlessly. As these devices and the associated software will pervade everyday life, an increasing number of software and hardware providers will deploy functionality in pervasive computing environments (PCE). That poses a very important interoperability issue, as it cannot be assumed that the various hardware and software components share common communication and data schemes. We argue that the use of Semantic Web technologies, namely the ontologies, present a intriguing way of resolving such issues and, therefore, their application in the deployment of PCE is a highly important research issue.

From Ontology Phobia to Contextual Ontology Use in Enterprise Information Systems

Shared understanding in an enterprise is necessary to permit a unifying framework serving as the basis of communication between people, interoperability between systems, and other system engineering benefits such as reusability, reliability, and specification. Bringing systems to work together is increasingly becoming essential for leveraging the Enterprise Information Systems (EIS) and reaching common goals. Currently, enterprises develop their systems independently with low consideration for the collaboration that systems can play with other systems. Certainly, semantic sharing represents the daunting barrier for making these systems work together through common shared understanding. In the last decade, theoretical research such as ontologies and context were suggested separately as formal support for treating the semantics-sharing problem. In order to resolve this main problem, we intend to pair up the two notions of Context and Ontologies. Typically, contextualization can be seen at the ontology level in order to enable the multiple views and multi-representation requirements. Hence, the formal representation of contextual ontologies should preserve adequate reasoning mechanisms. A machine understandable semantics and interpretation should be also given for information in a context, according to a specific system’s point of view. However, we perceived a growing ontology phobia in many enterprises. This fear is based on misunderstanding of ontologies’ advantages and lack of practical applications for theoretical proposals. The aim of this chapter is twofold. On one hand, it concentrates on studying the application of tightening together context and ontologies which can serve as formal background for reaching a suitable EIS environment. It invests in resolving the semantic-sharing problem between these systems. It focuses on suggesting a formalism for contextual ontologies based on a combination of Description Logics and Modal Logics. On the other hand, it investigates issues and arguments helping to overcome the ontology phobia. It shows with examples the usefulness of these contextual ontologies for resolving the semantic-sharing problem between some EIS.

Translating the Web Semantics of Georeferences

This chapter presents a review of the ways of georeferencing in Web resources, as opposed to the georeferencing of other information communities, specifically in route directions for wayfinders. The different information needs of the two information communities, reflected by their different semantics of georeferences, are identified. In a case study, we investigate the possibilities of translating the semantics of georeferences in Web resources to landmarks in route directions. We show that interpreting georeferences in Web resources enhances the perceivable properties of described features. Finally, we identify open questions for future research.

Dynamic Knowledge Discovery in Open, Distributed and Multi-Ontology Systems

In open distributed systems like peer-to-peer networks and Grids, many independent peers, possibly spanned across multiple organizations, need to share information resources (e.g., data, documents, services) provided by other nodes. By dynamic knowledge discovery we mean the capability of each node of finding knowledge in the system about information resources that, at a given moment, best match the requirements of a request for given target resource(s). The chapter will focus on describing models and techniques for ontology metadata management and ontology-based dynamic knowledge discovery in open distributed systems, by describing the architecture of a toolkit for information resource discovery and sharing developed in the Helios peer-based system.

Description of Policies Enriched by Semantics for Security Management

Policies, which usually govern the behavior of networking services (e.g., security, QoS, mobility, etc.) are becoming an increasingly popular approach for the dynamic regulation of Web information systems. By appropriately managing policies, a system can be continuously adjusted to accommodate variations in externally imposed constraints and environmental conditions. The adoption of a policy-based approach for controlling a system requires an appropriate policy representation regarding both syntax and semantics, and the design and development of a policy management framework. In the context of the Web, the use of languages enriched with semantics has been limited primarily to represent Web content and services. However the capabilities of these languages, coupled with the availability of tools to manipulate them, make them well suited for many other kinds of applications, as policy representation and management. In this chapter, we present an evaluation of the ongoing efforts to use ontological (Semantic Web) languages to represent policies for distributed systems.

Metadata- and Ontology-Based Semantic Web Mining

The increasing volume of data available on the Web makes information retrieval a tedious and difficult task. The vision of the Semantic Web introduces the next generation of the Web by establishing a layer of machine-understandable data, e.g., for software agents, sophisticated search engines and Web services. The success of the Semantic Web crucially depends on the easy creation, integration and use of semantic data. This chapter is a state-of-the-art review of techniques which could make the Web more “semantic”. Beyond this state-of-the-art, we describe open research areas and we present major current research programs in this domain.

A Comparison of Semantic Annotation Systems for Text-Based Web Documents

The Semantic Web promises new as well as extended applications, such as concept searching, custom Web page generation, and question-answering systems. Semantic annotation is a key component for the realization of the Semantic Web. The volume of existing and new documents on the Web makes manual annotation problematic. Semi-automatic semantic annotation systems, which we call platforms because of their extensibility and composability of services, have been designed to alleviate this burden for text-based Web documents. These semantic annotation platforms provide services supporting annotation, including ontology and knowledge base access and storage, information extraction, programming interfaces, and end-user interfaces. This chapter defines a framework for examining semantic annotation platform differences based on platform characteristics, surveys several recent platform implementations, defines a classification scheme based on information extraction method used, and discusses general platform architecture.

Contextual Ontology Modeling Language to Facilitate the use of enabling Semantic Web Technologies

A common approach to represent semantics on Semantic Web area is to use an ontology. However, there is an emerging approach that combines an ontology with its context definition. So, the misunderstanding can be avoided if the context is explicitly defined. The resulting structure is called contextual ontology. To process a contextual ontology at run time, it has to be expressed in a machine processable language. However, for the analysis and design phase of a Web domain, a more appropriate ontology modeling language is needed. To this aim, this chapter presents a metamodel for modeling explicit and formal contextual ontologies that assists Web domain designers in modeling contextual ontologies. Furthermore, the relationship between XML specifications and ontologies in order to add formal and explicit semantics to Web domain designs is analyzed.

Representation of Web Application Patterns in OWL

Patterns are distilled forms of knowledge from past experience and expertise in solving recurring problems in a domain. The Semantic Web provides an environment where the knowledge inherent in patterns can be adequately represented to be broadly accessible and be reasoned with. This chapter describes the process of creating OWAP, an ontology in the language OWL for Web Application Patterns. The problems faced in each phase and steps taken to resolve them are given. The significance and limitations of tools during OWAP design, implementation, and testing are outlined. The lessons learned in engineering OWAP are cast as an aggregated list of guidelines. Finally, some directions for future enhancements of OWAP are pointed out.

Ontology Management for Large-Scale Enterprise Systems

Semantic markup languages such as RDF (Resource Description Framework) (RDF, 1999) and OWL (Web Ontology Language) (OWL, 2004) are increasingly being used to externalize metadata or ontologies about data, software and services in a declarative form. Such externalized descriptions in ontological format are used for purposes ranging from search and retrieval to information integration and to service composition (RDF Projects, 2004; OWL Tools, 2004). Ontologies could significantly reduce the costs of deploying, integrating, and maintaining enterprise systems. The barrier to more widespread use of ontologies for such applications is the lack of support in the currently available middleware stacks used in enterprise computing. This chapter presents our work on developing an enterprise-scale ontology management system that will provide APIs and query languages, and scalability and performance that enterprise applications demand. We describe the design and implementation of the management system that programmatically supports the ontology needs of enterprise applications in a similar way to a database management system supporting the data needs of applications. In addition, we present a novel approach to representing ontologies in relational database tables to address the scalability and performance issues. The state of the art ontology management systems are either memory-based or use ad-hoc solutions for persisting data, and so provide limited scalability.