Perspective models as a means for achieving true representational accuracy

Accurate and expressive representation of the subject matter over which a context-oriented, decision-support system operates is fundamental to the effectiveness and longevity of the resulting solution. Often taking the form of an ontology, such extensive representational models, by their very nature, are rich in both relationships and fine-grained objects. It is, however, these two strengths that can significantly increase complexity for its users in addition to adversely affecting system performance. Further, due to the multitude of compartmentalized facets (i.e., populations of distinct, reasoning agents) inherent in such software solutions, it is important to recognize that a single-minded omniscient set of domain descriptions representing a singular view of the world is not necessarily appropriate for every ontology user. In fact, in such highly expressive environments, it is critical to not only accept these distinctions in user perspective, but to, in fact, promote and exploit them. It is by acknowledging and supporting this perspective-based individuality that true representational accuracy and utility is achieved. To be effective, the concept of perspective models must be partnered with a supportive model development process. In addition to an explanation of the concept of perspective models, this paper provides a discussion of a development process that supports effective development of both the potentially numerous set of perspective models in addition to the integration model that inter-connects them. The process offered in this paper effectively parcels the development of individual perspective models with the individuals possessing the necessary domain and use-case expertise. In this manner, the development process strives to significantly increase the involvement of the entire set of team members in the modeling activity, both capitalizing on user domain expertise in addition to increasing critical user understanding and acceptance of the representatio- - n over which their components are to operate