Abstract

This chapter presents first a historical review of the role of technological concepts and mathematical methods in the development of systems science, recalling the origins of systems analysis and the role of the hard and soft approaches to systems science. This dialectic contradiction is typical for Western science, but also helped to achieve many synthetic approaches and results, particularly proposed of researchers from either Eastern and Central Europe, or from Far East countries. In further sections, the chapter concentrates on the concepts of knowledge and of models on the verge of information society and knowledge-based economy. Knowledge-based economy and information society are defined similarly by knowledge and information becoming an essential or even dominant productive factor. In order to reflect on their impacts, it is essential to understand better the distinction between information and knowledge. Various types of understanding of the concept of knowledge are discussed in this chapter. One type characteristic of hard sciences in information age is related to synthesizing information into mathematical models that can be analyzed by using computers. Data mining in very large data sets is also related to finding patterns or models that synthesize characteristics of data relevant for a given purpose. Most of methodological conclusions related to mathematical modeling and data mining is not restricted to computer science, but have interdisciplinary character and support interdisciplinary research. Knowledge and information become either more commercialized in knowledge-based economy - or, if supported by public funding, more accessible for public use. Thus, it becomes also more important to make knowledge more accessible in the form of mathematical models used by various scientific disciplines. Easy exchange of computerized mathematical models will help in a better verification and validation of research results for knowledge-based economy and information society. However, in order to increase such accessibility, better standards and software tools for analysis of mathematical models should be developed. As an example, this chapter presents the need of such standards in a part of modern systems science - in multi-objective model-based decision support. A survey of reference point methodology and of its applications for model-based decision support systems in engineering and environmental control is included. Conclusions of the chapter relate to the concepts of knowledge and of models from mathematical, technological and humanistic perspectives and to the Western and Eastern traditions of understanding these concepts.

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