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Part-time +/or Distance Learning PhDs at KMi


Although the OU is famous for enabling students to undertake part-time distance learning, doing a PhD is very different to studying a predefined course. A PhD is an apprenticeship in learning a host of new skills 'on the job', and for this reason, most PhD students at the OU are full-time, on-site. In KMi you will get much more from the experience (and have a higher chance of success) if you working as part of a research group, and participating actively in the lab's life (e.g. seeing your supervisor regularly, joining the student group, meeting visiting researchers, giving presentations, and with ready access to high quality technology and internet access).

That being said, there are still part-time students at the OU because full-time study based here is of course not possible for everyone. Moreover, as collaboration technologies improve, some of the time/space obstacles to asynchronous research collaboration are reduced. However, the bottom line is: no supervisor, no PhD! If you can find a supervisor who is happy to take you on a part-time and/or distance learning basis, you're in business.

As explained on the main PhD/Studentship page, all students must write a research proposal, and you are strongly recommended to write this in conjunction with the potential supervisor. What you are recommended to do is look at the list of projects who are looking for students, and approach direct the relevant project leader of any that interest you. Briefly outline your background and interests, and see if they are interested to know more. You can of course send us a proposal out of the blue, but it stands less chance of finding a supervisor to own it.

The application deadline for Part-time study is the same as for Full-time applications.
 
The Open University Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Semantic Web and Knowledge Services is...


"The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation" (Berners-Lee et al., 2001).

Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...

Our aim is to be at the forefront of both theoretical and practical developments on the Semantic Web not only by developing theories and models, but also by building concrete applications, for a variety of domains and user communities, including KMi and the Open University itself.