Q-Active - Quantitative analysis of scientific and technological activities and networks

Problem definition and objective of the project:


The integration of digital technologies into science enables faster dissemination and exploitation of scientific knowledge. The research results are not only used in science, but they are implemented more quickly in process and product developments. The codification and digitization of scientific findings results annually in 1.9 million scientific publications in natural sciences, engineering and medicine. In addition, the complexity of the newly created knowledge increases significantly. New fields of knowledge appear at the boundaries of the established science areas, which are based on insights from several disciplines. Novel discoveries in emerging knowledge domains are raising the importance of new, previously unknown actors such as scientists and scientific institutions. As a result, new networks of actors emerge and develop and these actors might make an important contribution to technological innovation in the near future. Thus, these dynamic aspects in the science and innovation system should find consideration for the strategic orientation of science and business. Therefore, the prediction of technology dynamics is of considerable interest, but has not been methodically supported, yet. The aim of the project is to improve the methods for forecasting dynamics and interactions between research, technology development and innovation. In addition to the emergence of new knowledge areas and networks, we focus on the convergence processes of established sectors. The development and evaluation of the new methods initially takes place in the field of life sciences, which are characterized by pronounced dynamics and convergence. The additional application in economics enables a systematic comparison of the dynamics and convergence processes between the disciplines of science.


Empirical approach:


For the implementation of the project an interdisciplinary co-design approach is applied, which is realized through the cooperation of life sciences, economics and computer science. The analysis of heterogeneous networks of science and technology entities as well as the investigation of dynamic processes leading directly to the convergence of knowledge and technology are the core of the project. The foundation of the project are the methodological competencies of the consortium in text and data mining as well as network analysis and econometrics. This is combined with competencies in economic innovation research and a deep thematic anchoring in the life sciences. The existing theories of technology and industrial dynamics as well as semantic technologies and graph theory form the basis for the data integration and development of the forecasting methods.


Project support:

Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) für das Bundesministerium für Bildung und Forschung (BMBF)



CAU – Professur für Technologiemanagement  CAU Logo

ZBW – Leibniz-Informationszentrum Wirtschaft 

ZBW Logo
ZB MED – Informationszentrum Lebenswissenschaften  ZB MED


Prof. Dr. Carsten Schultz

Tetyana Melnychuk