Abstract
Developing useful intelligence on scientific and technological emergence challenges those who would manage R&D portfolios, assess research programs, or manage innovation. Recently, the U.S. Intelligence Advanced Research Projects Activity Foresight and Understanding from Scientific Exposition Program has explored means to detect emergence via text analyses. We have been involved in positing conceptual bases for emergence, framing candidate indicators, and devising implementations. We now present a software script to generate a family of Emergence Indicators for a topic of interest. This paper offers some background, then discusses the development of this script through iterative rounds of testing, and then offers example findings. Results point to promising and actionable intelligence for R&D decision-makers.
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Notes
When interpreting emergence results for patents users should be cognizant of the fact that a time-lag exists between the invention and innovation of the technology under study. While we have yet to fully explore the effect of this lag on emergence outcomes it is a noteworthy topic for future research.
We process the abstract records retrieved from databases, such as Web of Science, using VantagePoint desktop (Windows environment) software (www.theVantagePoint.com).
The script ran on the 13 k DSSC dataset used in this study in a matter of seconds.
Users can input data for derivative indicators from any field within the dataset they’re working with. In this paper we use fielded data at the author, organization and country level supplied by WOS. It’s up to the user’s discretion, however, to decide the inputs for these indicators. Different databases are likely to assign different definitions to the author, organization and country data they provide.
Average growth rate is calculated by subtracting the value associated with time period t from the value associated with time period t + 1, dividing the difference by the value associated with time period t and then taking the average of all results.
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Acknowledgements
This material is based upon work supported by the National Science Foundation under EAGER Award #: 1645237 for a Project, “Using the ORCID ID and Emergence Scoring to Study Frontier Researchers.” Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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Carley, S.F., Newman, N.C., Porter, A.L. et al. An indicator of technical emergence. Scientometrics 115, 35–49 (2018). https://doi.org/10.1007/s11192-018-2654-5
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DOI: https://doi.org/10.1007/s11192-018-2654-5