The Conceptual Design of an Expert System

Let us think abont how we can make a first hypothetical approach to what an expert system wonld constitnte. A standard model in the science of knowledge management is the knowledge pyramid, which basically describes the quantitative and logical relationship among data, information, knowledge, and action (please also refer to Fignre 2.1). 

Now that we have defined the basic terms, the next logical step would be to think about the transition from data to information, knowledge, and action. Let us select three methods for turning data into information calculation, analysis, and interpretation. Calculation and analysis can be appropriately performed using algorithms based on linear — or imperative — programming. There is also a series of software algorithms available for automatic interpretation of data in many cases, a human expert is even required to validate the results. In contrast to that, the transition of 

FIGURE 2.1 The relationship among data, information, knowledge, and action is described by the knowledge pyramid. The transition from data to information is performed by calculation, analysis, and interpretation performed by computer software, whereas in the transition from information to knowledge, human interpretation, experience, and intuition play a major role. The final step of reasoning leads to actions to be taken. Amount, context, and patterns can be considered as theoretical factors in contrast to that, real data have to be described by concepts of certainty, probability, and fuzziness. 

However, we have to face the fact that most data come from experimental observations. The results from these observations rarely underlie a linear and straightforward model experimental data exhibit certain fuzziness, usually as a result of the 

Taking these factors into account, we can now try to investigate the elementary 

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