  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.
