Paul R. Smart

Towards a knowledge-based approach to semantic service composition

The successful application of Grid and Web Service technologies to real-world problems, such as e-Science [1], requires not only the development of a common vocabulary and meta-data framework as the basis for interagent communication and service integration but also the access and use of a rich repository of domain-specific knowledge for problem solving. Both requirements are met by the respective outcomes of ontological and knowledge engineering initiatives. In this paper we discuss a novel, knowledge-based approach to resource synthesis (service composition), which draws on the functionality of semantic web services to represent and expose available resources. The approach we use exploits domain knowledge to guide the service composition process and provide advice on service selection and instantiation. The approach has been implemented in a prototype workflow construction environment that supports the runtime recommendation of a service solution, service discovery via semantic service descriptions, and knowledge-based configuration of selected services. The use of knowledge provides a basis for full automation of service composition via conventional planning algorithms. Workflows produced by this system can be executed through a domain-specific direct mapping mechanism or via a more fluid approach such as WSDL-based service grounding. The approach and prototype have been used to demonstrate practical benefits in the context of the Geodise initiative [2].

A Visual Approach to Semantic Query Design Using a Web-Based Graphical Query Designer

Query formulation is a key aspect of information retrieval, contributing to both the efficiency and usability of many semantic applications. A number of query languages, such as SPARQL, have been developed for the Semantic Web; however, there are, as yet, few tools to support end users with respect to the creation and editing of semantic queries. In this paper we introduce NITELIGHT, a Web-based graphical tool for semantic query construction that is based on the W3C SPARQL specification. NITELIGHT combines a number of features to support end-users with respect to the creation of SPARQL queries. These include a columnar ontology browser, an interactive graphical design surface, a SPARQL-compliant visual query language, a SPARQL syntax viewer and an integrated semantic query results browser. The functionality of each of these components is described in the current paper. In addition, we discuss the potential contribution of the NITELIGHT tool to rule creation/editing and semantic integration capabilities.

Context Aware Information Retrieval for Enhanced Situation Awareness

In the coalition forces, users are increasingly challenged with the issues of information overload and correlation of information from heterogeneous sources. Users might need different pieces of information, ranging from information about a single building, to the resolution strategy of a global conflict. Sometimes, the time, location and past history of information access can also shape the information needs of users. Information systems need to help users pull together data from disparate sources according to their expressed needs (as represented by system queries), as well as less specific criteria. Information consumers have varying roles, tasks/missions, goals and agendas, knowledge and background, and personal preferences. These factors can be used to shape both the execution of user queries and the form in which retrieved information is packaged. However, full automation of this daunting information aggregation and customization task is not possible with existing approaches. In this paper we present an infrastructure for context-aware information retrieval to enhance situation awareness. The infrastructure provides each user with a customized, mission-oriented system that gives access to the right information from heterogeneous sources in the context of a particular task, plan and/or mission. The approach lays on five intertwined fundamental concepts, namely Workflow, Context, Ontology, Profile and Information Aggregation. The exploitation of this knowledge, using appropriate domain ontologies, will make it feasible to provide contextual assistance in various ways to the work performed according to a users task-relevant information requirements. This paper formalizes these concepts and their interrelationships.

A Taxonomic Framework for Social Machines

Within the context of the World Wide Web, we have witnessed the emergence of a rich range of technologies that support both collaboration and distributed processing. Applications such as Wikipedia, for instance, have demonstrated the power and potential of the Web to facilitate the pooling of geographically dispersed knowledge assets. The result has been the creation of the world’s largest online encyclopedia, available for free in more than 200 languages for everyone to access and use.

The Cognitive Ecology of the Internet

In this chapter, we analyze the relationships between the Internet and its users in terms of situated cognition theory. We first argue that the Internet is a new kind of cognitive ecology , providing almost constant access to a vast amount of digital information that is increasingly more integrated into our cognitive routines. We then briefly introduce situated cognition theory and its species of embedded, embodied, extended, distributed and collective cognition. Having thus set the stage, we begin by taking an embedded cognition view and analyze how the Internet aids certain cognitive tasks. After that, we conceptualize how the Internet enables new kinds of embodied interaction , extends certain aspects of our embodiment, and examine how wearable technologies that monitor physiological, behavioral and contextual states transform the embodied self. On the basis of the degree of cognitive integration between a user and Internet resource, we then look at how and when the Internet extends our cognitive processes. We end this chapter with a discussion of distributed and collective cognition as facilitated by the Internet.

AKTiveSA: A Technical Demonstrator System For Enhanced Situation Awareness

The issue of improved situation awareness is a key concern for military agencies, promising to deliver strategic advantages in a variety of conflict and non-conflict scenarios. Improved situation awareness can benefit operational effectiveness by facilitating the planning process, improving the quality and timeliness of decisions, and providing better feedback regarding the strategic consequences of military actions. In this paper, we aim to show how a combination of semantic technologies and user interface design initiatives can be used to improve situation awareness in a simulated humanitarian relief scenario. We describe the development of a technical demonstrator system, the AKTiveSA TDS, which integrates a variety of knowledge technologies and visualization components within the context of a unitary application framework. We also describe our approach to scenario development, knowledge acquisition, ontology engineering, and system design. Some specific problems encountered during system development are discussed, e.g. the performance overheads associated with rules-based processing, and potential solution strategies for these problems are presented alongside a description of future development activities.

Knowledge-based information fusion for improved situational awareness

This project aims to investigate knowledge-based approaches to the problem of information fusion. We show how domain-specific knowledge, in conjunction with semantic Web services, can be used to improve situational awareness in the operational deployment of humanitarian operations, especially when such operations occur against a contextual backdrop of ongoing military conflict. Information, harvested from a variety of physically disparate and semantically heterogeneous data sources, is used to establish a common repository of semantically rich, conceptual-level representations of real-world events. Reasoning services, deployed over the knowledge repository, are used to intelligently fuse information, taking into account factors such as the level of trust and confidence assigned to specific information sources. Selective attention to information of relevance to particular users helps avoid situations of information overload that might otherwise result from the information fusion process. We believe this approach to have general applicability in a wide variety of military contexts.

An Analysis of the Origin of Ontology Mismatches on the Semantic Web

Despite the potential of domain ontologies to provide consensual representations of domain-relevant knowledge, the open, distributed and decentralized nature of the Semantic Web means that individuals will rarely, if ever, countenance a common set of terminological and representational commitments during the ontology design process. More often than not, differences between ontologies are likely to occur, and this is the case even when the ontologies describe identical or overlapping domains of interest. Differences between ontologies are often referred to as ontology mismatches and there is an extensive research literature geared towards the technology-mediated reconciliation of such mismatches. Our approach in the current paper is not to comment on the relative merits or demerits of the various technological solutions that could be used to resolve ontological differences; rather, we aim to explore the reasons why such differences may arise in the first place. In addition to a review of the various factors that contribute to ontology mismatches on the Semantic Web, we also discuss a number of focus areas for future research in this area. An improved understanding of the origins of ontology mismatches will, we argue, complement existing research into semantic integration techniques. In particular, by understanding more about the complex cognitive, epistemic and socio-cultural factors associated with the ontology development process, we may be able to develop knowledge acquisition and modeling tools/techniques that attenuate the impact of ontology mismatches for large-scale information sharing and data integration on the Semantic Web.

Approaching Semantically-Mediated Acoustic Data Fusion

Our primary hypothesis is that it should be possible to enrich data fusion by semantic processing, with wide potential application. In order to achieve our aim we need to represent the semantic data and enable reasoning about it in a framework that can be aligned with data fusion. Ontologies are most suited to this task as they allow for rich representation of data structure; some approaches include probabilistic representation. These can be aligned with data fusion approaches, such as Bayesian, which can fuse by including estimates of uncertainty. We shall describe our initial approaches towards establishing our hypothesis, including a survey of the enabling technologies, a description of application data (acoustic sensors, military scenario), and our new method of feature selection for acoustic data fusion. We also explore the semantic attributes and the representations that can be deployed for enrichment purposes, showing how ontologies can be used in this context. In these respects we shall show how we can approach enrichment of data fusion by semantic technologies, how this can capitalise on the current stock of techniques, and illustrate the potential benefits associated with this new approach.

Collective Sensemaking and Military Coalitions

Sense making is a key capability for military coalitions. It lets both individuals and teams make sense of conflicting, ambiguous, and uncertain information. Computational modeling provides one means of improving our understanding in this area.