The developed world is awash with sensors. However, they are typically locked into unimodal closed systems. To unleash their full potential, access to sensors should be opened such that their data and services can be integrated with data and services available in other information systems, facilitating novel applications and services that are based on the state of the real world. We describe our vision and architecture of a Semantic Web of Things: a service infrastructure that makes the deployment and use of semantic applications involving Internet-connected sensors almost as easy as building, searching, and reading a web page today.

Wireless Sensor Networks (WSNs) have yet to reach their full potential. WSN applications are currently built as closed uni-modal systems. In this paper we describe our efforts in the SPITFIRE project [1] to unlock the true potential of the sensor world. Our approach combines technologies from the Internet of Things and the Semantic Web [2]. To central idea is to build a software infrastructure to connect sensors to the Internet, publish their output in well-understood formats on the Web, and integrate the resulting realtime state information about the real-world with other data sources from the Web

This paper describes the output of a multi-year project to build a cross industry concurrent design platform. The platform, known as the Open Concurrent Design Server (OCDS), was initially built to support the space mission feasibility analysis at the European Space Agency (ESA). The vision however is to build a platform that could support concurrent design across a broad range of complex engineering tasks from Shipbuilding to Oil & Gas exploration.

This paper describes the output of a multi-year project to build a cross industry concurrent design platform. The platform, known as the Open Concurrent Design Server (OCDS), was initially built to support the space mission feasibility analysis at the European Space Agency (ESA). The vision however was to build a platform that could support concurrent design across a broad range of complex engineering tasks from Shipbuilding to Oil & Gas exploration.

IMS ARCS is an Industrial and Academic cooperative program conducting research in the area of IMS technology with a view to creating a body of intellectual property for the use of the project partners, and serving as a case study on how to develop IMS application software. This paper outlines the objectives of the project, how the research work was planned and executed, and how it intends to transfer knowledge to its industry partners and create a route to allow commercialisation of the research work. The paper also describes how a set of exemplar IMS services and enabler prototypes are being developed to showcase the research work and provide examples of how such services may be developed for commercial purposes. The prototypes will also demonstrate the capabilities of IMS, such as location and presence information, and sophisticated call control. The project employs the OpenIMS testbed from Fraunhofer Fokus, as the basis for the development and execution of the prototypes.

Legacy information systems typically form the backbone of the information flow within an organisation and are the main vehicle for consolidating information about the business. As a solution to the problems these systems pose brittleness, inflexibility, isolation, non-extensibility, lack of openness etc. many companies are migrating their legacy systems to new environments which allow the information system to more easily adapt to new business requirements. This paper presents a survey of research into Migration of Legacy Information Systems. The main problems that companies with legacy systems must face are analysed, and the challenges possible solutions must solve discussed. The paper provides an overview of the most important currently available solutions, and their main downsides are Jesus Bisbal, Deirdre Lawless, Ray Richardson, Donie O’Sullivan, Bing Wu, Jane Grimson, Vincent Wade, Broadcom Eireann Research, Trinity College, Dublin, Ireland. Dublin, Ireland.

Research into Artificial Intelligence, and specifically Distributed AI has identified agent technology as offering a key role in future systems. The technology does not discriminate by application area, and is equally applicable to wrapping legacy technologies and systems as it is to implementing new systems. The Intelligent Systems Group at Broadcom éireann Research Ltd. has been investigating the suitability of Intelligent Agents (IAs) as an enabling technology for a unifying approach to network and service management systems. Such an approach should support network management, service management and service delivery in a seamless manner, to best satisfy an operator's business needs. This paper catalogues the work done into the use of IA technologies within each of these management areas and on the integration of software components and legacy systems. This work has employed an open, distributed, language-independent multi-agent platform known as the Agent Services Layer (ASL), which was developed by Broadcom éireann Research's Intelligent Systems Group. The architecture of this platform and experiences gained on its application to the above mentioned problem domains are outlined.

The use of Semantic Web Service (SWS) technologies have been suggested to enable more dynamic B2B integration of heterogeneous systems and partners. We present our approach to accomplish dynamic B2B integrations based on the WSMX SWS environment. We particularly show how WSMX can be made to support the RosettaNet e-business framework and how it can add dynamics to B2B interactions by automating mediation of heterogeneous messages. This is illustrated through a purchasing scenario. The benefits of applying SWS technologies include more flexibility in accepting heterogeneity in B2B integrations and easing back-end integrations. This allows for example to introduce more competition into the purchasing process within e-business frameworks.

The trends for pushing more operational intelligence towards network elements to achieve more context-aware and self-managing behavior often requires elements to gather network knowledge without necessarily binding explicitly to all of the potential sources of that knowledge. Though event-based publish-subscribe models allow efficient distribution of knowledge where the event types are known globally, dynamic service chains, ad hoc networks and pervasive computing application all introduce a more fluid and heterogeneous range of context knowledge. This requires some runtime translation of knowledge between sources and sinks of network context. This paper builds on existing mapping techniques that use ontological forms of existing management information models to examine the extent to which these can be employed for runtime semantic interoperability for network knowledge. It presents results in developing a management knowledge delivery framework based on existing models and platforms, but which offers a more decentralized knowledge exchange mechanism

The problems posed by mission-critical legacy systems-e.g., brittleness, inflexibility, isolation, non-extensibility, lack of openness-are well known, but practical solutions have been slow to emerge. Generally, organisations attempt to keep their legacy systems operational, while developing mechanisms which allow the legacy systems to interoperate with new, modern systems which provide additional functionality. The most mature approach employs gateways to provide this interoperability. However, gateways introduce considerable complexity in their attempt to maintain consistency between the legacy and target systems. This paper presents an innovative gateway-free approach to migrating legacy information systems in a mission-critical environment: the Butterfly Methodology. The fundamental premise of this methodology is to question the need for the parallel operation of the legacy and target systems during migration.

The widespread use of computer technology over several decades has resulted in some large, complex systems which have evolved to a state where they significantly resist further modification and evolution. These Legacy Information Systems are normally mission-critical : if one of these systems stops working the business may grind to a halt. Thus for many organisations, decommissioning is not an option. An alternative solution is Legacy System Migration which has recently become an important research and practical issue. This paper presents an approach to mission-critical legacy systems migration: Butterfly methodology. Data migration is the primary focus of Butterfly methodology, however, it is placed in the overall context of a complete legacy system migration.

Legacy information systems typically form the backbone of the information flow within an organisation and are the main vehicle for consolidating information about the business. These systems also pose considerable problems: brittleness, inflexibility, isolation, nonextensibility, lack of openness etc., the so called legacy system problem which opens up a new research topic, legacy system migration. This paper provides a brief review of the main issues involved in legacy information systems migration.

• the systems cannot evolve to provide new functionalities required by the organisation • they run on obsolete hardware which is expensive to maintain and reduces productivity due to the low speed of the old hardware • maintenance is expensive, tracing failures is costly and time consuming due to the lack of documentation and a general lack of understanding of the internal workings • integration efforts are greatly hampered by the absence of clean interfaces

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In this paper we develop a conceptual distance measure between words based on a large thesaurus. The area in which we work is data sharing in large scale autonomous distributed database systems. It is clear that neither the tightly nor loosely coupled federated database (FDBS) approaches to data sharing scale up adequately, however, of the two approaches, it seems the problems posed by the loosely coupled approach are more manageable. These problems are centred on the complexity involved for users of loosely coupled systems, namely the requirement that users have a knowledge of data locations and relationships. In our research we propose a system which alleviates these complexities. The system, referred to as FEDDICT, could be described as an active federated dictionary and will store information on the location of data sets within the FDBS and on semantic relationships existing between these data sets.In light of die issues raised due to the size of the environment the problems of locating and relating individual data sets are tackled at the concept level. Users are thus allowed to refer to information of interest in terms familiar to them. Hierarchical concept graphs (HCGs) reused as a common frame of reference and a conceptual similarity measure is developed as a method of comparison.