Fig 2.1 to 2.3 show the extended concept maps with the windows displaying associated graphics when invoked by a ‘mouse over’ on the concept node.

Fig 2.1 Natural Drainage information associated with the concept map on sewarage/ drainage

Fig 2.2 Information on digital terrain and habitation/ settlement associated with the concept map

Fig 2.3 Thematic maps used with concept map tools in Knowledge repository
3. Knowledge Exploration and Representation
Knowledge representation is often characterized as an optimized depiction of a number of possible ways in which to present the concepts and their interrelationships. The domain exploration may be enacted in the users mental model by following several strategic shortcuts and viewing from multiple perspectives, often by expanding on concept nodes or collapsing them to vary the patterns of associations. Insights, experiences and past associations are frequently used during the knowledge build process as also in the use of the knowledge model for problem solving. Knowledge building is increasingly seen as a distributed and collaborative activity.
Design and development of a strategic intervention for problem solving within a knowledge domain is a complex activity. The process for design of solution is often characterized as a top-down breadth-first search of the space of possible solutions. Problem solvers need to be adept at generating and evaluating a range of candidate solutions to a problem.
The manner in which the knowledge exploration and problem solving process proceeds determines the optimality of the solution that is constructed to the initial problem specification.
Fig 3.1 gives the conceptual block diagram of the digital repository and how extended concept maps could be used with a knowledge repository.

Fig 3.1 Conceptual block diagram of the knowledge repository
Collaborative building of a knowledge repository and its refinement involves early commitment to, and refining of, a suboptimal representation of the domain. Strategic knowledge is usually developed though trial and error iterative mode. Much of what the knowledge builder knows is gained through feedback on experience.