A generalized conceptual development for the analysis and flow of information

A generalized framework for developing analytical and conceptual relationships involving the flow of information has previously been suggested. This paper provides further refinement, rigor, and extension for some of the earlier relationships suggested. In particular, a measure of the amount of information is defined as the difference of the value of the decision state of the decision‐maker after and before receipt of the message. This measure is universally applicable for all information that is concerned with the effectiveness of the message upon the recipient. It is accordingly called pragmatic information. The definition is a direct consequence of the interdependence between information and decision‐making and of the definition that information is data of value in decision‐making. In order to evaluate this measure of information, it is convenient to use a generalized information system model which has previously been proposed and which has virtually universal applicability. The use of this model permits the evaluation of the measure of information in terms of the reduction of uncertainty to a decision maker. Six different types of uncertainty are identified. Specifically, a type of uncertainty which is generally overlooked in the decision‐making literature is found to be important. This is called executional uncertainty. It is pointed out that the information science aspects of decision theory must cover comprehensively those decision‐makers who not only are expert but those decision‐makers who may be mediocre or even rather poor. Although any decision rule may be utilized in terms of the framework outlined, a suggested rule which is convenient and reasonable is proposed for evaluating the decision state of a decision‐maker at any point in time. The measure of information suggested is situation, time, and decision‐maker dependent. The framework and relationships developed are an important step toward the development of a true theory of information science. It is further suggested that each data set or document might have some average (over time) amount of information content for a decision‐maker of any given “effectiveness”. The relationship of this average amount of information as a function of the decision‐maker effectiveness is suggested as an important functional relationship that exists for every document. It is called an information profile of that document or data set. A typical information profile is suggested.