Combining inductive and deductive inference in knowledge management tasks

This paper indicates how different logic programming technologies can underpin an architecture for distributed knowledge management in which higher throughput in information supply is achieved by a (semi-)automated solution to the more challenging problem of knowledge creation. The paper first proposes working definitions of the notions of data, knowledge and information in purely logical terms, and then shows how existing technologies can be combined into an inference engine, referred to as a knowledge, information and data engine (KIDE), integrating inductive and deductive capabilities. The paper then briefly introduces the notion of virtual organizations and uses the set-up stage of virtual organizations to exemplify the value-adding potential of KIDEs in knowledge management contexts