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Tech Report kmi-03-01 Abstract


Semantic Layering with Magpie
Techreport ID: kmi-03-01
Date: 2003
Author(s): John Domingue, Martin Dzbor, Enrico Motta
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Browsing the web involves two main tasks: finding the right web page and then making sense of its content. A significant amount of research has gone into supporting the task of finding web resources through ‘standard’ information retrieval mechanisms, or semantics-enhanced search. Much less attention has been paid to the second problem. In this paper we describe Magpie, a tool which supports the interpretation of web pages. Magpie acts as a complementary knowledge source, which a reader can call upon to quickly gain access to any background knowledge relevant to a web resource. Magpie works by automatically associating an ontology based semantic layer to web resources, allowing relevant services to be directly invoked within a standard web browser. The functionality of Magpie is illustrated using examples of how it has been integrated with our lab’s web resources.

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An amended version of this report will appear as a chapter in the book on 'Ontologies in Information Systems' authored by Rudi Studer and Steffen Staab to be published by Springer Verlag soon.
 
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Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.