Generality and scale are important but difficult issues in knowledge engineering. At the root of the difficulty lie two hard questions: how to accumulate huge volumes of knowledge, and how to support heterogeneous knowledge and processing? One answer to the first question is to reuse legacy knowledge systems, integrate knowledge systems with legacy databases, and enable sharing of the databases by multiple knowledge systems. We present an architecture called HIPED for realizing this answer. HIPED converts the second question above into a new form: how to convert data accessed from a legacy database into a form appropriate to the processing method used in a legacy knowledge system? One answer to this reformed question is to use method-specific transformation of data into knowledge. We describe an experiment in which a legacy knowledge system called INTERACTIVE KRITn<: is integrated with an OR ACLE database using IDI as the communication tool. The experiment indicates the computational feasibility of method-specific data-to knowledge transformations.
From Data to Knowledge: Method-Specific Transformations
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