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Decision makers considering policy or strategy related to the development of emerging technologies expect high quality data on the support for different technological options in order to track trends and allocate resources. A natural starting point would be R&D funding statistics. This paper explores the limitations of such aggregated data in relation to the substance and quantification of funding for emerging technologies. Using biotechnology as an illustrative case, we test the utility of a novel taxonomy to demonstrate the endemic weaknesses in the availability and quality of data from public and private sources. Using the same taxonomy, we consider the extent to which tech-mining presents an alternative, or potentially complementary, way to determine support for emerging technologies using proxy measures such as patents and scientific publications. We find that using proxy measures provides additional visibility of technological emergence and suggest these are a useful complement to financial data. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamics of expectations from a cognitive semantic perspective, specifically the relationship between epistemological asymmetry and uncertainty. Building on the work of several other authors since the 1980s, we propose a new framework based on frame semantics for discovering and organizing information related to expectations. When this framework is applied to two sets of expectations surrounding the applications of RNA interference, a recently discovered molecular genetic phenomenon with increasing notoriety, uncertainty seems to be correlated with what we call conceptual distance, the difference between past/present and future aspects of expectations. In essence, levelling of epistemological asymmetry through frame semantic analysis can decrease or increase uncertainty based on conceptual distance from previously fulfilled expectations. [ABSTRACT FROM AUTHOR]