This Small Grant for Exploratory Research (SGER) will support a pilot study that compares traditional disciplinary divisions to two natural classification systems: one based on a journal classification system and the other based on an article-level classification system. The first task will focus on mapping and comparing existing conventional classification systems: the structure of chemistry funding organizations, and two different journal classification systems. The remaining tasks will develop and characterize an article-level classification system. Ten years of article-level data will be clustered into paradigms (groups of highly cited references). The dynamic structure of chemistry will then be explored using both retrospective and prospective approaches, both of which will generate Ptrends, or clusters of paradigms over time. Results from these two approaches will be compared to identify early indicators of emerging trends. Third, grants will be linked to paradigms to Ptrends to show the funding patterns for different dynamic structures. Hypotheses about how funding correlates with different types of dynamic structures will be tested. Results from many of the computations will be reviewed and/or compared by experts in chemistry to provide a judgment on their accuracy or applicability.
The results of this bibliometric analysis will be widely reported though publications and a sequence of high quality maps that show the disciplinary sub-structure of chemistry and its dynamics over time. This project will develop and test algorithms to generate scientific structures that, along with appropriate visualizations, have the potential to change the way science is funded, organized and tracked. This will have timely and positive implications for R&D managers, policy makers, educational institutions, and corporations.
