Career guidance knowledge is heavily context dependent and dynamic. It is fed on the one hand by formalized information (such as labor market information), and on the other hand by heavily context dependent experiences of career advisors who put this knowledge into use with their clients and other constituencies, and within the community of career advisors themselves.

Semantic Media Wiki Technology was chosen to address these challenges because it offers

1. the ease of dynamic and collaborative updating of content, and
2. the possibility to capture context of use with semantic technologies.

The constant evolution of career guidance knowledge, its context dependence and its fluctuation between informal and formal modes makes it a prime example for study within the MATURE context. Semantic Media Wiki technology for the same reason offers a suitable proposition for supporting and researching semantic and content maturing.

The main goal is to explore the potential of use of this approach for knowledge maturing in the context of career guidance. At this stage, we are more interested in exploring applicability of general principles of knowledge maturing, rather than applicability of specific technologies.

User interface functionalities that exted the Semantic Media Wiki in terms of searching, collaborating, adding semantic markup and visualization will enhance the usability for practitioners. In addition, we will develop extensions that make use of services from a text mining and information extraction framework in order to provide intelligent services for maturing semantic structures and contents.

The resulting system will be demonstrated to a group of practitioners who will be able to explore it in the context of a scenario which they should be able to relate to easily. This will help us to explore the general principles of the approach and its applicability to career guidance practice and knowledge maturing.
 

Know Miner	Search	Visualization