IRS support for OWL-S and WSMO
This event took place on Monday 21 June 2004 at 12:30
Dr Farshad Hakimpour KMi, The Open University
There is a great deal of work on developing ontologies (such as OWL-S and WSMO) for describing semantics of Web Services. IRS is one of the few existing systems (if not the only one) to support the Semantic Web Services technologies. I will show how the underlying model of IRS (i.e. Task-PSM ontology) could support parts of OWL-S, as well as how we modified and extended the task-PSM ontology to be able to support features of OWL-S. I will also present further capability the Task-PSM ontology provides, in comparison to OWL-S. I will briefly describe the status of the current work for supporting WSMO.
Download PowerPoint Presentation (614 KB ZIP file)
This event took place on Monday 21 June 2004 at 12:30
Dr Farshad Hakimpour KMi, The Open University
There is a great deal of work on developing ontologies (such as OWL-S and WSMO) for describing semantics of Web Services. IRS is one of the few existing systems (if not the only one) to support the Semantic Web Services technologies. I will show how the underlying model of IRS (i.e. Task-PSM ontology) could support parts of OWL-S, as well as how we modified and extended the task-PSM ontology to be able to support features of OWL-S. I will also present further capability the Task-PSM ontology provides, in comparison to OWL-S. I will briefly describe the status of the current work for supporting WSMO.
Download PowerPoint Presentation (614 KB ZIP file)
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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.
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