Ontologies are a key component for building open and dynamic distributed pervasive computing systems in which agents and devices share contextual information. We describe our use of the Web Ontology Language OWL and other tools for building the foundation ontology for the Context Broker Architecture (CoBrA), a new context-aware pervasive computing framework. The current version of the CoBrA ontology models the basic concepts of people, agents, places, and presentation events in an intelligent meeting room environment. It provides a vocabulary of terms for classes and properties suitable for building practical systems that model context in pervasive computing environments. We also describe our ongoing research in developing an OWL inference engine using Flora-2 and in extending the present CoBrA ontology to use the DAML spatial and temporal ontologies.

The idea of weaving technology into the backdrop of natural human interactions is a long-standing vision [1]. To realize that dream, a number of technologies need to be developed. Distributed software systems need to allow large numbers of software components to locate and communicate with one another. Interfaces between humans and computers need to enable natural, unencumbered interaction. Environments need to be aware of what users are trying to do so that they can offer appropriate assistance. Intelligent tools and applications need to be built on top of these components. The Intelligent

We present an agent-based system for capturing and indexing software design meetings. During these meetings, designers design object-oriented software tools, including new agent-based technologies for the Intelligent Room, by sketching UML-type designs on a white-board. To capture the design meeting history, the Design Meeting Agent requests available audio, video, and screen capture services from the environment and uses them to capture the entire design meeting. However, finding a particular moment of the design history video and audio records can be cumbersome without a proper indexing scheme. To detect, index, and timestamp significant events in the design process, the Tahuti Agent, also started by the Design Meeting Agent, records, recognizes, and understands the UML-type sketches drawn during the meeting. These timestamps can be mapped to particular moments in the captured video and audio, aiding in the retrieval of the captured information. Metaglue, a multi-agent system, provides the computational glue necessary to bind the distributed components of the system together. It also provides necessary tools for seamless multi-modal interaction between the varied agents and the users.

An expressive representation for location is an important component in many applications. However, while many location-aware applications can reason about space at the level of coordinates and containment relationships, they have no way to express the semantics that define how a particular space is used. We present lair, an ontology that addresses this problem by modeling both the geographical relationships between spaces as well as the functional purpose of a given space. We describe how lair was used to create an application that produces walking directions comparable to those given by a person, and a pilot study that evaluated the quality of these directions. We also describe how lair can be used to evaluate other intelligent user interfaces.

Building smart meeting rooms requires the support of a computing system architecture. In this paper, we describe the Context Broker Architecture (CoBrA), a broker-centric agent architecture for pervasive contextaware systems. CoBrA exploits the Web Ontology Language OWL for supporting knowledge sharing and data fusion, uses logic inferences for resolving and detecting inconsistent context knowledge, and provides users with a policy language to control their private information. Central to CoBrA is an intelligent broker agent that maintains a share model of context for all agents, services, and devices in the space, and protects users’ privacy by enforcing the policy rules that they have defined. We also describe the use of CoBrA ontologies, context reasoning mechanisms, and privacy protection in a smart meeting room system called EasyMeeting.

Abstract. This paper describes SOUPA (Standard Ontology for Ubiquitous and Pervasive Applications) and the use of this ontology in building the Context Broker Architecture (CoBrA). CoBrA is a new agent architecture for supporting pervasive context-aware systems in a smart space environment. The SOUPA ontology is expressed using the Web Ontology Language OWL and includes modular component vocabularies to represent intelligent agents with associated beliefs, desire, and intentions, time, space, events, user profiles, actions, and policies for security and privacy. Central to CoBrA is an intelligent broker agent that exploits ontologies to support knowledge sharing, context reasoning, and user privacy protection. We also describe two prototype systems that we have developed to demonstrate the feasibility and the use of CoBrA. 1.

The increasing complexity of pervasive computing environments puts the current software development methods to the test. There is a large variation in different types of hardware that need to be addressed. Besides, there is no guarantee the environment does not evolve, making the software developed for the initial environment deprecated and in need for updates or reconfiguration. Software deployed in such an environment should be sufficiently dynamic to cope with new environment configurations, even while the system is in use. This goes beyond coping with new contexts of use and building context-aware systems: while most approaches are mainly focused on how the software behavior adapts according to the changing context in a fixed environment, our approach, ReWiRe, allows the environment configuration to change over time. 1

This article presents a framework for incorporating commonly used VR (Virtual Reality) databases for graphics and physics simulation into an AI (Artificial Intelligence) knowledge base using a unifying semantic net (SN) representation. Several examples in the area of multimodal interaction for AI based graphics applications are given to motivate this approach. An evaluation of the chosen SN knowledge representation (KR) regarding five roles suitable to analyze a given KR is followed by a discussion about resulting conceptual and technical requirements for the underlying DB/KBMS (database/knowledge base management system) which supports the chosen KR as well as mediating layers for external simulation relevant modules.

A great challenge in information visualization today is to provide models and software that effectively integrate the graphics content of scenes with domain-specific knowledge so that the users can effectively query, interpret, personalize and manipulate the visualized information [1]. Moreover, it is important that the intelligent visualization applications are interoperable in the semantic web environment and thus, require that the models and software supporting them integrate state-of-the-art international standards for knowledge representation, graphics and multimedia. In this paper, we present a model, a methodology and a software framework for the semantic web (Intelligent 3D Visualization Platform -- I3DVP) for the development of interoperable intelligent visualization applications that support the coupling of graphics and virtual reality scenes with domain knowledge of different domains. The graphics content and the semantics of the scenes are married into a consistent and cohesive ontological model while at the same time knowledge -based techniques for the querying, manipulation, and semantic personalization of the scenes are introduced. We also provide methods for knowledge driven information visualization and visualization -aided decision making based on inference by reasoning.

Abstract. This paper presents a proposal of a context-based architecture to achieve the required synergy among the ubiquitous computing devices of an intelligent environment. These devices produce context information that models the behaviour of the environment. This context information is the glue among the devices and the context-aware applications. The generated context information provides a common view of the world. A blackboard architecture allows to share this context information and a context model is proposed to represent it. A prototype of such a smart room has been developed, including several devices as well as a set of context-aware demonstrators. They work together employing the context information stored on the blackboard. 1