From: Borner, Katy <katy@indiana.edu>
Call for Papers for a special issue of Scientometrics on:
"Simulating the Processes of Science, Technology, and Innovation"
Deadline: 30th November 2015
Motivation
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 special issue calls for models which predict/forecast the structure and/or dynamics of STI. The focus 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. New insights about STI can be gained by comparing and relating different kinds of models, including data, statistical, observational, psychological and computational. This special issue aims to present a state of the art in terms such computational models.
Submission Deadlines
Please feel free to contact the editors with paper proposals. Submit full papers by 30th November 2015. Reviews will become available begin of January 2016. Final papers are due February 29, 2016.
Special Issue Editors
- Bruce Edmonds, Professor of Social Simulation, Centre for Policy Modelling, Manchester Metropolitan University, UK.
- Andrea Scharnhorst, Royal Netherlands Academy of Arts and Sciences, Data Archiving and Networked Services, Amsterdam, Netherlands
- Katy Börner, ILS, SOIC, Indiana University, USA and Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands
- Stasa Milojevic, ILS, SOIC, Indiana University, USA
Some Background References
· Edmonds, B., Gilbert, N., Ahrweiler, P. & Scharnhorst, A. (2011) Special Issue of the Journal of Artificial Societies and Social Simulation on 'Simulating the Social Processes of Science' 14,(4) (Introduction to special issue is at: http://jasss.soc.surrey.ac.uk/14/4/14.html).
· Moss, S. and Edmonds, B. (2005) Sociology and Simulation: Statistical and Qualitative Cross-Validation, American Journal of Sociology, 110(4) 1095-1131.
· Ahrweiler, Petra, Nigel Gilbert and Andreas Pyka, eds. 2015. Joining Complexity Science and Social Simulation for Innovation Policy. Cambridge Publishers.
· Scharnhorst, Andrea, Katy Börner, and Peter van den Besselaar, eds. 2012. Models of Science Dynamics: Encounters Between Complexity Theory and Information Science. Springer Verlag.
· Watts, Christopher and Nigel Gilbert. 2014. Simulating Innovation. Computer-based Tools for Re-Thinking Innovation. London: Edward Elgar.
-- Katy Borner Victor H. Yngve Professor of Information Science Director, CI for Network Science Center, http://cns.iu.edu Curator, Mapping Science exhibit, http://scimaps.org ILS, School of Informatics and Computing, Indiana University Wells Library 021, 1320 E. Tenth Street, Bloomington, IN 47405, USA
