The difficulty of maintaining effective testbed partnerships, among users of computer-based tools and builders of those tools, has been an obstacle to the success of science collaboratories. Testbed partnerships are as essential for knowledge-tool advancement as that advancement is to the support of effective partnerships, because knowledge tools must be instituted in a context that truly augments (rather than merely tries to replicate) human inference in collaborative contexts. We propose a game framework for engaging content-tool users and context-tool developers in testbed partnerships, and an architecture for modular knowledge-tool integration, as initial steps in the effective advancement of knowledge capture and improvement of testbed partnerships.

The Conceptual Programming environment, CP, being developed at New Mexico State University (NMSU), is a complete knowledge representation programming environment for use with both dynamic, open-world, problem solving (weak) applications and static, closed-world, scientific analysis (strong) applications. CP is based upon a graphical methodology of visualization derived from John Sowa's conceptual graph theory. In this paper, we describe the formal basis for the internal CP representation and explain the mechanisms for the operators relating to the processing of time, space and constraints within the CP environment. The CP environment is a ‘working’ representation system, and makes a good foundation for suitable applications