Scientometric Mappings as Strategic Intelligence For
Tentative Governance of Emerging Science and Technologies
Daniele Rotolo 1, Ismael Rafols 1,2, Michael Hopkins 1, Loet Leydesdorff 3
1SPRU (Science and Technology Polocy Research), University of Sussex - Falmer, Brighton - BN1 9SL - United Kingdom
2Ingenio (CSIC-UPV), Universitat Politècnica de València - Camí de Vera, s/n - València - 46022 - Spain
3Amsterdam School of Communication Research (ASCoR), University of Amsterdam - Kloveniersburgwal 48, Amsterdam - 1012 CX - The Netherlands
Working Paper (Version presented at the 2013 DRUID Conference - the new version is forthcoming)
We discuss the use of scientometric mapping and overlay techniques as providing ‘strategic intelligence’ for the definition of ‘tentative’ government arrangements that aim to address the rapid dynamics and uncertainties of Emerging Science and Technologies (ESTs). We show the potential of these techniques in informing analysts about relevant dynamics of ESTs across the geographical, social, and cognitive spaces of emergence in a timely and relatively comprehensive manner. Specifically, by shedding light on these spaces as well as on combinations of them, the mappings may reveal the set of both intentional and un-intentional, arrangements that are established in the emergence of novel science and technologies, i.e. the de facto governance. Flexibility within and across databases and granularity in the levels of analysis make the scientometric overlays a ‘distributed’ tool of strategic intelligence, i.e. the integration and comparison of results from different contexts facilitates the discussion for developing informed perspectives. Our argument relies on three empirical studies of ESTs in the biomedical domain: RNA interference (RNAi), Human Papilloma Virus (HPV), and Thiopurine Methyltransferase (TPMT) testing technologies. These ESTs are analysed longitudinally by using a range of mapping techniques and multiple sources of data.
Key words: maps and overlays; de facto governance; emerging science and technology; scientometrics; case study.
|Spaces of Emergence
The authors acknowledge the support of UK Economic and Social Research Council (award RES-360-25-0076 - “Mapping the Dynamics of Emergent Technologies”) in the development of the case studies. The authors are also grateful the US National Science Foundation (award No. 1064146 - “Revealing Innovation Pathways: Hybrid Science Maps for Technology Assessment and Foresight”) for the support in the development of the mapping techniques. The authors are grateful to Stefan Kuhlmann and the participants of the 2013 Eu-SPRI Conference, 2013 DRUID Conferefence, and 2013 Atlanta Conferences for their constructive feedbacks on a previous version of the article. The findings and observations contained in this paper are those of the authors and do not necessarily reflect the funders’ views.