The common vision of pervasive computing environments requires a very large range of devices and software components to interoperate seamlessly. From the assumption that these devices and associated software permeate the fabric of everyday life, a massive increase looms in the number of software developers deploying functionality into pervasive computing environments. This poses a very large interoperability problem for which solutions reliant solely on interoperability standards will not scale. An interoperability problem of a similar scale is presented by the desire for a Semantic Web supporting autonomous machine communication over the WWW. Here, solutions based on service-oriented architectures and ontologies are being actively researched, and we examine how such an approach could be used to address pervasive computing's interoperability problem. The paper outlines the potential role that semantic techniques offer in solving some key challenges, including candidate service discovery, intelligent matching, service adaptation and service composition. In particular the paper addresses the resulting requirement of semantic interoperability outlining initial results in dynamic gateway generation. In addition the paper proposes a roadmap identifying the different scenarios in which semantic techniques will contribute to the engineering and operation of pervasive computing systems.

Integration of geographic information has increased in importance because of new possibilities arising from the interconnected world and the increasing availability of geographic information. Ontologies support the creation of conceptual models and help with information integration. In this paper, we propose a way to link the formal representation of semantics (i.e., ontologies) to conceptual schemas describing information stored in databases. The main result is a formal framework that explains a mapping between a spatial ontology and a geographic conceptual schema. The mapping of ontologies to conceptual schemas is made using three different levels of abstraction: formal, domain, and application levels. At the formal level, highly abstract concepts are used to express the schema and the ontologies. At the domain level, the schema is regarded as an instance of a generic data model. At the application level, we focus on the particular case of geographic applications. We also discuss the in¯uence of ontologies in both the traditional and geographic systems development methodologies, with an emphasis on the conceptual design phase. Keywords: systems ontologies, geographic conceptual models, geographic data modeling, geographic information 1.

Past decade saw much hype in the area of information technology. The emerging of semantic Web makes us ask if it is another hype. This paper focuses on its potential application in Internet commerce and intends to answer the question to some degree. The contributions are: first, we find and examine twelve potential advantages of applying semantic Web for Internet commerce; second, we conduct a case study of eprocurement in order to show its advantages for each process of e-procurement; lastly, we identify critical research issues that may transfer the potential advantages into tangible benefits.

The array of devices, networks and resources available in pervasive computing environments, or smart spaces, will require effective self-management systems controlled via user-level policies. However, the local nature of smart spaces means that they present a potentially huge increase in the number of and nature of management domains, e.g. representing individual homes, shops, businesses, schools, hospitals etc. However, differences in local domain models and local resource models means that policies relevant to one smart space will often use different semantics for subject and target objects compared to other pervasive computing domains. To allow users to capture personal preferences in terms of policies that can be consistently applied as they roam between smart spaces, the semantic interoperability problem resulting from different models for policy subjects and targets must be overcome. In this paper we present a framework where the use of ontology-based semantics for policy elements allows dynamic ontology mapping capabilities to support policy mobility. We demonstrate its operation with a case study showing policy mobility in a policy-driven smart space management system.

Abstract. In this paper we describe some commonly-required functionality for constructing, visualizing and manipulating ontologies. These make extensive use of XML and DOM technologies. The functions developed are based on practical applications needing access to distributed statistical databases and intelligent content management. They fulfill the needs identified as new features for next generation ontology development and application. These system features have been implemented in Java and JAXP. 1

Abstract. In this paper we describe a visual, ontology-based query paradigm. It has two novel features: visually specifying aggregate table queries and table layout in a single process, and providing users with an ontology guide for formulating statistical data analysis tasks as table queries which are composed of the terms defined in ontologies. We describe the role of the fundamental concept of ontology in the content representation of distributed databases with large numbers of multi-valued attributes, along with the methods and techniques developed for representing and manipulating ontologies, and for understanding semantics of database contents and query formulation and processing. 1.

We present an approach for the semantic integration of geoscience data, and a system implementing this approach. Specifically, we demonstrate the use of data ontologies and application of markup languages for semantic integration of data and services. We introduce a domain level object ontology, called Earth and Planetary ONTology (EPONT) to explore, extract, and integrate information from heterogeneous geologic data sets. As proof of concept, we define the DIA engine, an extensible infrastructure for the Discovery, Integration, and Analysis of geoscience data, tools, and services. DIA provides a collaborative environment where scientists can share their resources (e.g., geochemical data, filtering services, etc.) by registering them through well-defined ontologies. We envision the DIA infrastructure to also use other classes of ontologies, namely process and service, for knowledge creation.