Scientific research is a major driving force in a knowledge based economy. Income, health and wellbeing depend on scientific progress. The better we understand the inner workings of the scientific enterprise, the better we can prompt, manage, steer, and utilize scientific progress. Diverse indicators and approaches exist to evaluate and monitor research activities, from calculating the reputation of a researcher, institution, or country to analyzing and visualizing global brain circulation. However, there are very few predictive models of science that are used by key decision makers in academia, industry, or government interested to improve the quality and impact of scholarly efforts. We present a novel 'bibliographic bibliometric' analysis which we apply to a large collection of books relevant for the modelling of science. We explain the data collection together with the results of the data analyses and visualizations. In the final section we discuss how the analysis of books that describe different modelling approaches can inform the design of new models of science.
|Title of host publication||Theories of Informetrics and Scholarly Communication|
|Editors||Cassidy R. Sugimoto|
|Number of pages||38|
|Publication status||Published - 2016|