Strategic Intelligence on Emerging Technologies: Scientometric Overlay Mapping
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http://data.d4science.org/ctlg/RISIS2OpenData/dedup_wf_001--49813fc234a36e8acb2dcc2c0e59ceef |
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Identity
Access Modality
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Access Right | Open Access |
Attribution
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Author | Daniele Rotolo, 0000-0001-8077-9840 |
Author | Ismael Ràfols, 0000-0002-6527-7778 |
Contributor | Universitat Politècnica de València. Instituto de Gestión de la Innovación y del Conocimiento - Institut de Gestió de la Innovació i del Coneixement |
Contributor | ASCoR Other Research (FMG) |
Contributor | Economic and Social Research Council (UK) |
Contributor | National Science Foundation (US) |
Publishing
Field | Value |
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Collected From | Digital.CSIC; RiuNet; ORCID; Datacite; figshare; UnpayWall; arXiv.org e-Print Archive; NARCIS; Crossref; Microsoft Academic Graph; CORE (RIOXX-UK Aggregator) |
Hosted By | Universiteit van Amsterdam Digital Academic Repository; Digital.CSIC; RiuNet; Sussex Research Online; figshare; arXiv.org e-Print Archive; NARCIS; Journal of the Association for Information Science and Technology |
Publication Date | 2015-01-01 |
Publisher | figshare |
Additional Info
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Country | Netherlands; United Kingdom; Spain |
Description | This paper examines the use of scientometric overlay mapping as a tool of “strategic intelligence” to aid the governing of emerging technologies. We develop an integrative synthesis of different overlay mapping techniques and associated perspectives on technological emergence across geographical, social, and cognitive spaces. To do so, we longitudinally analyze (with publication and patent data) three case studies of emerging technologies in the medical domain. These are RNA interference (RNAi), human papillomavirus (HPV) testing technologies for cervical cancer, and thiopurine methyltransferase (TPMT) genetic testing. Given the flexibility (i.e., adaptability to different sources of data) and granularity (i.e., applicability across multiple levels of data aggregation) of overlay mapping techniques, we argue that these techniques can favor the integration and comparison of results from different contexts and cases, thus potentially functioning as a platform for “distributed” strategic intelligence for analysts and decision makers. |
Description | The authors acknowledge the support of the 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 also thank the US National Science Foundation (award #1064146—“Revealing Innovation Pathways: Hybrid Science Maps for Technology Assessment and Foresight”) for support in the development of the mapping techniques. |
Description | Peer Reviewed |
Format | application/pdf |
Language | UNKNOWN |
Resource Type | Other literature type; Preprint; Article |
system:type | publication |
Management Info
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Source | https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::49813fc234a36e8acb2dcc2c0e59ceef |
Author | jsonws_user |
Last Updated | 25 December 2020, 23:40 (CET) |
Created | 25 December 2020, 23:40 (CET) |