Aggregating Operational Knowledge in Community Settings

Abstract

In a community setting, operational knowledge or “knowledge that works,” refers to knowledge elements that can be put to use. This can be contrasted with encyclopedic knowledge or “knowledge that tells” that sets the background shared mental model among members of a population. Given any community, large amounts of operational knowledge are routinely diffused through social connections. While current day social media catalyzes such diffusion, they are not primarily suited to capture and represent knowledge. This paper argues that operational knowledge aggregation is in some sense, the opposite of encyclopedic knowledge aggregation. The latter is a convergent process that aggregates different local views into a global view; while the former is a divergent process, where common knowledge gets segregated into several local worlds of utilitarian knowledge. If the community as a whole is coherent, these different worlds end up denoting different aspects of the community’s dynamics. Local worlds are not independent of one another and characteristics of one local world affect characteristics of other local worlds. To capture this phenomenon, a data model called Many Worlds on a Frame (MWF) is proposed, that is detailed in this paper.