Abstract
In system modeling, knowledge management comes vividly into the picture when dealing with a collection of models. These models, being considered as sources of knowledge, are engaged in some collective pursuits of collaboration and consensus formation. We show the use of information granules in these processes by elaborating on their conceptual role. It is revealed that information granules are used to facilitate processes of collaboration and consensus building. Such granular constructs, referred to as granular models, can also emerge as a part of higher order models to reflect and quantify the diversity of the sources of knowledge involved in knowledge management. Several detailed algorithmic schemes are presented, along with related computational aspects associated with Granular Computing. It is also shown how the construction of information granules, through the use of the principle of justifiable granularity, becomes advantageous in the realization of granular models. This study builds upon seminal concepts established in L.A. Zadeh’s Rosetta Stone paper devoted to information granulation.