Alistair Duke

OntoShare: a knowledge management environment for virtual communities of practice

An ontology-based knowledge sharing system OntoShare and its evaluation as part of a case study is described. RDF(S) is are used to specify and populate an ontology, based on information shared between users in virtual communities. We begin by discussing the advantages that use of Semantic Web technology afford in the area of knowledge management tools. The way in which OntoShare supports WWW-based communities of practice is described. Usage of OntoShare semi-automatically builds an RDF-annotated information resource for the community (and potentially for others also). Observing that in practice the meanings of and relationships between concepts evolve over time, OntoShare supports a degree of ontology evolution based on usage of the system - that is, based on the kinds of information users are sharing and the concepts (ontological classes) to which they assign this information. A case study involving OntoShare was carried out. The evaluation exercise for this case study and its results are described. We conclude by describing avenues of ongoing and future research.

Next generation knowledge access

Purpose – The paper shows how access to knowledge can be enhanced by using a set of innovative approaches and technologies based on the semantic web.Design/methodology/approach – Emerging trends in knowledge access are considered followed by a description of how ontologies and semantics can contribute. A set of tools is then presented which is based on semantic web technology. For each of these tools a detailed description of the approach is given together with an analysis of related and future work as appropriate.Findings – The tools presented are at the prototype stage but can already show how knowledge access can be improved by allowing users to more precisely express what they are looking for and by presenting to them in a form that is appropriate to their current context.Research limitations/implications – The tools show promising results in improving access to knowledge which will be further evaluated within a practical setting. The tools will be integrated and trialled as part of case studies withi...

Squirrel: An Advanced Semantic Search and Browse Facility

Search is seen as a key application that can benefit from semantic technology with improvements to recall and precision over conventional Information Retrieval techniques. This paper describes Squirrel, a search and browse tool that provides access to semantically annotated data. Squirrel provides combined keyword based and semantic searching. The intention is to provide a balance between the speed and ease of use of simple free text search and the power of semantic search. In addition, the ontological approach provides the user with a much richer browsing experience. Squirrel builds on and integrates a number of semantic technology components. These include machine learning and information extraction components which generate, extract and manage semantic metadata contained within and about textual documents at index time. A number of run-time components have also been integrated to deliver an enhanced user experience which goes beyond merely presenting a list of documents as a query response. The tool has been trialled and evaluated in two case studies and we report early results from this exercise, revealing promising results.

Ontology-based question answering for digital libraries

In this paper we present an approach to question answering over heterogeneous knowledge sources that makes use of different ontology management components within the scenario of a digital library application. We present a principled framework for integrating structured metadata and unstructured resource content in a seamless manner which can then be flexibly queried using structured queries expressed in natural language. The novelty of the approach lies in the combination of different semantic technologies providing a clear benefit for the application scenario considered. The resulting system is implemented as part of the digital library of British Telecommunications (BT). The original contribution of our paper lies in the architecture we present allowing for the nonstraightforward integration of the different components we consider.

A Semantic Service Orientated Architecture for the Telecommunications Industry

A Service Orientated Architecture will allow organisations to enhance interoperability and encourage reuse of components and interfaces. In this paper, the application of semantic descriptions to services is advocated with the aim of further improving the SOA and enabling scalability. An application of Semantic Web Services for the Telecommunications Industry is described. It shows how services components forming part of a Service Orientated Architecture can be described semantically in terms of shared data and process ontologies. The potential benefits of this approach are explored. A use case is presented that illustrates how the efficiency of a telecommunications system designer can be improved with the use of Semantic Web Services.

Towards b2b integration in telecommunications with semantic web services

This paper describes BT Wholesales B2B Gateway as an approach to provide Business-to-Business integration within the Telecommunications sector. Although the Gateway provides increased efficiency over separate systems, the process to allow business partners to integrate is lengthy and costly. The application of Semantic Web Services will ease the integration process. The Web Services Modelling Ontology is described and applied to the Gateway. The paper presents the initial requirements of the Gateway upon WSMO and proposes how WSMO could provide further benefit in the future.

Telecommunication Mashups Using RESTful Services

Evolution in the telecommunications sector has led to companies within it providing APIs for their products and services, allowing others to build communication services into their own service offerings. In order to support mass adoption of this new approach, consumers of these APIs (many of which are RESTful) must be supported by a reduction in the complexity involved with describing, finding, composing and invoking them. Existing efforts to provide automation have, in general, focused on WSDL services rather than REST services. The paper explores the approach of the SOA4All project in supporting interaction with REST services which is being applied in a telecommunications focused case study.

Semantically Enhanced Search and Browse

Squirrel, a search and browse tool that provides access to semantically annotated data is described. The tool offers a hybrid approach to search allowing the user to enter simple search terms and then refine their search or browse to related material through the presentation of appropriate metadata. Squirrel builds upon and integrates a number of the semantic technology components described elsewhere in the book. These include machine learning and information extraction components which generate, extract and manage semantic metadata contained within and about textual documents at index time. A number of run-time components have also been integrated to deliver an enhanced user experience such as natural language generation which provides natural language summaries of knowledge held in formal (ontological) structures; device independence which allows the tool to be run on multiple devices; result consolidation which presents the most relevant textual content of result documents rather than a simple list of results; and a natural language interface which translates natural language queries into structured queries formulated with respect to a given ontology.

Hypercat RDF: Semantic Enrichment for IoT

The rapid growth of sensor networks and smart devices has led to the generation of an increasing amount of information. Such information typically originates from various sources and is published in different formats. One of the key prerequisites for the Internet of Things (IoT) is interoperability. The Hypercat specification defines a lightweight JSON-based hypermedia catalogue, and is tailored towards the existing needs of industry. In this work, we propose a semantic enrichment of Hypercat, defining an RDF-based catalogue. We propose an ontology that captures the core of the Hypercat RDF specification and provides a mapping mechanism between existing JSON and proposed RDF properties. Finally, we propose a new type of search, called Semantic Search, which allows SPARQL-like queries on top of semantically enriched Hypercat catalogues and discuss how this semantic approach offers advantages over what was previously available.

Travel Time Prediction on Highways

We describe the development of a predictive model for vehicle journey time on highways. Accurate travel time prediction is an important problem since it enables planning of cost effective vehicle routes and departure times, with the aim of saving time and fuel while reducing pollution. The main information source used is data from roadside double inductive loop sensors which measure vehicle speed, flow and density at specific locations. We model the spatiotemporal distribution of travel times by using local linear regression. The use of real-time data is very accurate for shorter journeys starting now and less reliable as journey times increase. Local linear regression can be used to optimally balance the use of historical and real time data. The main contribution of the paper is the extension of local linear models with higher order autoregressive travel time variables, namely vehicle flow data, and density data. Using two years of UK Highways Agency (HA) loop sensor data we found that the extended model significantly improves predictive performance while retaining the main benefits of earlier work: interpretability of linear models as well as computationally simple predictions.