Structures and Regularities of Knowledge Flows

The systemic view of science leads for example to a subdivision in natural sciences, human sciences and structural sciences. Especially in the field of natural sciences like physics or chemistry there are formal descriptions to assess and calculate the value of these parameters, to describe their structure, and to identify their impact and influence on other objects. This article examines analogous to these natural scientific (physical and chemical) processes the similarities to the knowledge processes, which belong to the human science and have primarily sociological and psychological origins. The basic assumption in this context is the idea of knowledge nodes. Knowledge nodes are individuals or smallest possible combinations of organizational units / individuals. They are turning into knowledge networks based on scientific or business-oriented motivations for cross-linking and increasing their knowledge power. The knowledge nodes consist of knowledge potentials of various knowledge domains. These knowledge potentials can be assessed by their size and by the priority or importance. The knowledge potential existing in the creation phase of the knowledge node will not keep its value along the timeline. There is a kind of half life of knowledge, and the thesis, that knowledge potentials of knowledge nodes reduce or lose their level or value against other knowledge nodes if they do not develop and extend their knowledge. Therefore, every knowledge node tries to open and make accessible new knowledge sources. The development of knowledge takes place on the one hand by the exchange of knowledge within the knowledge node (as far as it consists of more than one individual) and the exploitation of explicit knowledge of external sources. On the other hand, there is the need for compensating and exchanging the knowledge potentials with other knowledge nodes. Thus, knowledge flows occur. This knowledge exchange is characterized by a structure, this means in the IT sense it is a protocol by which the exchange runs. The quantity and kind of exchanged knowledge will be determined by rules and regularities, including filters and restrictions. The structure of these knowledge flows, and the rules under which they run, are very difficult to measure. Thus, it is also not quit trivial to define them. Therefore, it is the aim of this paper, to develop an approach for defining the structure, rules and restrictions on knowledge flows between knowledge nodes. This model provides a fundamental concept for the further analysis of knowledge networks and the lifecycle of knowledge nodes. It forms an important basis for the understanding and hence for the assessability of knowledge flows and finally knowledge networks.