Ontological Versus Knowledge Engineering

Abstract

This paper opens with a nearly obligatory remark about the difference between a knowledge base (KB) and a database (DB). This seems to hinge on the “gray box” versus “black box” nature of the entries. The paper then discusses the need for a huge KB to break today’s bottleneck in intelligent systems: their brittleness when confronted by unforseen problems. That same brittleness—the “representation trap”—is what prevents multiple expert systems from cooperating or even sharing rules. Then comes the central question of this paper: how is the task of building a huge KB different from building n small KB's? This takes us into the realm of ontological engineering, and we find that the key is to take that word—engineering—seriously. Namely, there is no single elegant “use-neutral” solution to the problem, at least not in this century, but a kind of varigated “tool-box” approach might succeed. © 1989, SDAIEEE. All rights reserved.