Forecasting science: Models of science and technology dynamics for innovation policy

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Date(s) - 29/06/2015
2:00 pm - 5:00 pm

Boğaziçi University

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  • Katy Börner (Indiana University, USA)
  • Andrea Scharnhorst (KNAW, The Netherlands)
  • Stasa Milojevic (Indiana University, USA)
  • Petra Ahrweiler (Director and CEO, EA European Academy of Technology and Innovation Assessment GmbH, Bad Neuenahr-Ahrweiler, Germany)
  • David Chavalarias (Centre d’Analyses de Mathématiques Sociales (CAMS), Ecole des Hautes Etudes en Sciences Sociales (EHESS), Director of the Complex Systems Institute of Paris Ile-de-France, Paris, France)
  • Santo Fortunato, Professor of Complex Systems of the Department of Biomedical Engineering and Computational Science (BECS) of the School of Science of Aalto University in Espoo, Finland
  • Advisor: Nicolay Vitanov (Professor, Institute of Mechanics, Bulgarian Academy of Sciences, Alexander von Humboldt Fellow)

Summary: In a knowledge-based economy, science and technology are omnipresent and their importance is undisputed. Equally evident is the need to allocate resources (both monetary and labor) in an effective way to foster innovation. In the last decades, science policy has embraced scientometrics to gain insights into the structure and evolution of science and devised diverse metrics and indicators. However, it has not invested significant efforts into modelling the dynamics of science, technology, and/or innovation (STI) (mathematically, statistically, and computationally). While it may not be possible to predict the nature and essence of the next scientific or technological innovation, it is often possible to predict the circumstances leading to it, i.e., where it is most likely to happen and under which conditions. Some examples are: Which career paths are more likely to lead to high impact works? Which funding system has the highest return on investments? Which institutions will be most productive over the next years? This workshop invites the community of researchers working on models of STI to both share their latest research and collectively create a roadmap to foster future modeling efforts. Extended abstracts are solicited for presentation and will be reviewed by the workshop organizing committee. We specifically seek models which predict/forecast the structure and/or dynamics of STI. The focus of the workshop is on mathematical, statistical, and computational models, but we do not exclude qualitative models as long as they can be used to develop scenarios of future STI dynamics.

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