Writing a PhD proposal for submitting to the Knowledge Media Institute.

Note: Proposals are not wholly binding. They can (and must) change as the research progresses. They do, though, help us to work out (a) who might be appropriate supervisors, (b) how well you have thought out a small piece of research, and (c) roughly the kind of project you intend to tackle, and how you intend to tackle it. And that's really what the proposal is for.
1. Talk to us in advance
We are allowed, and even encouraged, to help you prepare a proposal in advance. This allows you and potential supervisors to negotiate a common interest in the topic of your research. If you don't contact us in advance, it is more than likely that we won't be able to find potential supervisors with this common interest.
If you require a studentship grant you must write a proposal targetting one of the Projects seeking a PhD student and contact the project leader direct. However, if you have your own source of funding, or other ideas which are synergistic with KMi's research themes ideas, feel free to contact the relevant project leader direct. You can also contact Dr Paul Mulholland [email] with a 1-2 page draft outline, and he will try to put you in touch with relevant KMi staff (or possibly other faculties).
2. Structure the proposal
Before actually writing the proposal, it's a good idea to do a bit of research on what other people have done, and to find a nice clear statement of a problem that you are interested in tackling.
We find that targeted proposals - ones with a clear statement of a particular problem and possible solution, or a clear system to build - tend to be much easier to write proposals about than open research topics. It is important that a proposal doesn't seem at all vague. If the proposal seems to read confidently, that will help it to be successful.
3. Cover the "big four" issues
A good proposal covers four main issues. These look like answers to these four questions:
- What am I going to do in my research?
- Who else has done research like this, and what did they do?
- How am I going to do this research?
- Why will this research be important to the academic community?
A good proposal will have answers to all these questions, usually spending about half to two thirds of a page on each one.
4. Attend to the method
The other important part of a proposal is for us to get a clear idea of how you intend to pursue the proposed research. Questions that might be addressed in this section include:
- Am I going to build a system?
- What tools am I going to use to build it?
- How am I going to find evidence as to whether it is a good system?
5. Select proposal references carefully
An important part of the proposal, as we've just discussed, is the background against which you are proposing to work. A good way of representing this is to carefully choose some of the more important academic papers that discuss this, and properly refer to them in your proposal. You are allowed (and even encouraged) to be constructively critical of this work if you intend to build on it.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
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.
Check out these Hot Semantic Web and Knowledge Services Projects:
List all Semantic Web and Knowledge Services Projects
Check out these Hot Semantic Web and Knowledge Services Technologies:
List all Semantic Web and Knowledge Services Technologies
List all Semantic Web and Knowledge Services Projects
Check out these Hot Semantic Web and Knowledge Services Technologies:
List all Semantic Web and Knowledge Services Technologies



