KMi Seminars
PhD Skills
This event took place on Monday 12 September 2005 at 10:00

Prof. Brigid Heywood PVC Research and Staff, The OU

PhD Skills is web-based scheme to support OU research students in developing the skills they will need to pursue and complete their doctorates successfully and on time. Crucially, it will enable us to fulfil our obligations under the revised QAA Code of Practice for PhD students in readiness for the QAA audit in December.

This year the scheme is in its pilot phase, and will be available to our new intake of full- and part-time students at their induction conference on 11th September. Supervisors play a crucial role in their students' skills development, and so the scheme has been designed to actively enable their participation - and to save them work by putting information at their fingertips.

The other key feature of the scheme is that it is designed to work at three different levels of specificity:
  1. Generic;
  2. Faculty/ Research Centre; and
  3. Discipline/Department/Research Group

The briefing
This briefing is for staff such as Heads of Department, Associate Deans of Research and Directors of Graduate Studies. Its purposes are to:
  • demonstrate the scheme, explain its functions and show how it links to the new arrangements for probation assessment for PhD students;
  • show how the scheme can be customised at the three different levels of specificity, and enable work to start on this task (i.e. Faculties and Departments to tailor the information supplied to students to their specific needs and opportunities).
  • prompt Faculties, Research Groups and Departments to begin informing, training and supporting their supervisors.
Click to download the PowerPoint slides

 
KMi Seminars
 

Multimedia and Information Systems is...


Multimedia and Information Systems
Our research is centred around the theme of Multimedia Information Retrieval, ie, Video Search Engines, Image Databases, Spoken Document Retrieval, Music Retrieval, Query Languages and Query Mediation.

We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.

Visit the MMIS website