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Tech Report kmi-01-14 Abstract


Beyond Rigid KA Metatools: An Initial Proposal for a KR-Independent, Adaptive, Customizable, Ontology-based KA Metatool
Techreport ID: kmi-01-14
Date: 2001
Author(s): Yuangui lei, Enrico Motta and John Domingue
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This paper proposes a new knowledge-acquisition metatool, KRIACO, a Web-based, Knowledge Representation Independent, Adaptive, Customizable, Ontology-based Knowledge Acquisition Metatool, which aims to overcome sorts of shortcomings of current knowledge acquisition metatools. To achieve its goal, KRIACO will adopt OKBC as an underlying knowledge representation model to overcome the restriction caused by a specific knowledge representation system. It will use an ontology-driven tool specification approach to specify the domain and the task models; an interface ontology and a declarative interface model to drive the interface design and customization process; adaptive approach to provide flexible, adaptive user interfaces. This paper discusses these approaches in detail and presents the framework of KRIACO.
 
KMi Publications Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

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.