Trust on the Web: Some Web Science Research Challenges

Web Science is the interdisciplinary study of the World Wide Web as a first-order object in order to understand its relationship with the wider societies in which it is embedded, and in order to facilitate its future engineering as a beneficial object. In this paper, research issues and challenges relating to the vital topic of trust are reviewed, showing how the Web Science agenda requires trust to be addressed, and how addressing the challenges requires a range of disciplinary skills applied in an integrated manner

All about that - a URI profiling tool for monitoring and preserving linked data

All About That (AAT) is a URI Profiling tool which allows users to monitor and preserve Linked Data in which they are interested. Its design is based upon the principle of adapting ideas from hypermedia link integrity in order to apply them to the Semantic Web. As the Linked Data Web expands it will become increasingly important to maintain links such that the data remains useful and therefore this tool is presented as a step towards providing this maintenance capability

An Opportunistic Approach to Adding Value to a Photograph Collection

The Semantic Web can, among other things, be used for photograph annotation. Many implementations of this idea exist, but all are limited by the fact that a human must manually create the annotations for the photographs, often using a program with which he or she is not familiar. This poster discusses an opportunistic method of photograph annotation that uses logical inference in conjunction with existing data from various sources in order to obtain information about the images being annotated

DC Proposal: Evaluating trustworthiness of web content using semantic web technologies

Trust plays an important part in people's decision processes for using information. This is especially true on the Web, which has less quality control for publishing information. Untrustworthy data may lead users to make wrong decisions or result in the misunderstanding of concepts. Therefore, it is important for users to have a mechanism for assessing the trustworthiness of the information they consume. Prior research focuses on policy-based and reputation-based trust. It does not take the information itself into account. In this PhD research, we focus on evaluating the trustworthiness of Web content based on available and inferred metadata that can be obtained using Semantic Web technologies. This paper discusses the vision of our PhD work and presents an approach to solve that problem

What do they think when we stack them in? A comparative analysis of student perceptions relating to large and small marketing subjects

University education is in a period of flux with emphasis being focused on quality education, competition for students both local and international as well as changes in governmental financial support and direction. It is with this scenario as a backdrop, that universities in an endeavour to obtain economies of scale offer subjects with large student enrolments. This study investigates marketing students&rsquo; perception of and participation in marketing subjects relating to teaching quality, staff availability and support, and individual student involvement in marketing education with large enrolments compared to subjects with small enrolments. This research builds on the investigations of effects of class size by Cuseo (2004) and Binney et al (2004). The study used a multi-method approach. Data from a sample of 621 students was analysed using Factor analysis, MANOVA and ANOVA. Students indicated that there was little difference in the quality of learning obtained in small or large classes. Of interest from a marketing perspective, however, is the perception by students that they are more likely to obtain practical assistance and support from tutors in smaller classes. Student perceptions generally show no major differences between large and small classes in relation to subject selection, ability to learn and lecture&nbsp; attendance. Students expressed a preference for the opportunity to choose from a number of lecture streams available in subjects with large enrolments. Of interest, however is the student belief that they are less likely to actively participate in large lectures than in small lecture environments.<br /

SemWeB Semantic Web Browser – Improving Browsing Experience with Semantic and Personalized Information and Hyperlinks

Imagine a Web browser that can understand the context of a Web page and recommends related semantic hyperlinks in any Web domain. In addition, imagine this browser also understands your browsing needs and personalizes information for you. The aim of our research is to achieve this in open Web environment using Semantic Web technologies and adaptive hypermedia techniques. In this paper, we discuss a novel Semantic Web browser, SemWeB, which utilizes linked data for context-based hyperlink recommendation and uses a behavior-based and an ontology-driven user modeling architecture for personalization on Web documents. The aim of this research is to bring the gap between the technology and user needs using Semantic Web technologies in Web browsing

The Semantic Web Revisited

The original Scientific American article on the Semantic Web appeared in 2001. It described the evolution of a Web that consisted largely of documents for humans to read to one that included data and information for computers to manipulate. The Semantic Web is a Web of actionable information--information derived from data through a semantic theory for interpreting the symbols.This simple idea, however, remains largely unrealized. Shopbots and auction bots abound on the Web, but these are essentially handcrafted for particular tasks; they have little ability to interact with heterogeneous data and information types. Because we haven't yet delivered large-scale, agent-based mediation, some commentators argue that the Semantic Web has failed to deliver. We argue that agents can only flourish when standards are well established and that the Web standards for expressing shared meaning have progressed steadily over the past five years. Furthermore, we see the use of ontologies in the e-science community presaging ultimate success for the Semantic Web--just as the use of HTTP within the CERN particle physics community led to the revolutionary success of the original Web. This article is part of a special issue on the Future of AI

Government as a social machine in an ecosystem

The Web is becoming increasingly pervasive throughout all aspects of human activity. As citizens and organisations adopt Web technologies, so governments are beginning to respond by themselves utilising the electronic space. Much of this has been reactive, and there is very little understanding of the impact that Web technologies are having on government systems and processes, let alone a proactive approach to designing systems that can ensure a positive and beneficial societal impact. The ecosystem which encompasses governments, citizens and communities is both evolving and adaptive, and the only way to examine and understand the development of Web-enabled government, and its possible implications, is to consider government itself as a “social machine” within a social machine ecosystem. In this light, there are significant opportunities and challenges for government that this paper identifies