Information theory and information science†

The empirical import of Shannon's Information Theory and its impact on information science are discussed. It is argued that extension of the scope of Information Theory as well as development of new theories of information science presupposes better understanding of relevant empirical regularities and laws. Possibilities of broadening the empirical foundation of Information Theory by introduction of appropriate least effort criteria are discussed.     

Some approaches to modeling complex information systems

State-of-the-art of modeling complex information systems is briefly discussed. A distinction is made between macrolevel and microlevel modeling of such systems. Modeling approaches and techniques, appropriate for each of these two levels are described and assessed.     

Fire-relevant literature and its availability

The primary goal of the National Fire Data Center which was authorized by the U.S. Congress on 29 October 1974 is “the selection, analysis, publication and dissemination of information related to the prevention, occurrence, control, and results of fires of all types” (Section 9a, Public Law 93–498). In pursuing this goal it was clearly necessary to determine the relevance and usefulness to fire researchers of the many computerized bibliographic data bases which already exist in support of science and technology, and to assess the extent to which existing computerized bibliographic data bases can provide information relevant to fire research. We describe here the results of a study which was directed at this particular problem.     

Information theory and information science2

The empirical import of Shannon's Information Theory and its impact on information science are discussed. It is argued that extension of the scope of Information Theory as well as development of new theories of information science presupposes better understanding of relevant empirical regularities and laws. Possibilities of broadening the empirical foundation of Information Theory by introduction of appropriate least effort criteria are discussed.     

Predictive models of information systems

The problem of modelling information systems is studied with focus on predictability. Predictability presupposes discovery and knowledge of empirical laws and theories, which are in the domain of information science. Discovery of such laws and theories goes hand in hand with the development of the capability to measure important variables in that domain. The state-of-the-art of predictive modelling is discussed with respect to syntactic, semantic, and pragmatic criteria, emphasizing the need for concentrated effort in further development of the empirical foundation of information science.