Modelling the Structure and Dynamics of Science Using Books

TL;DR

This paper introduces a novel bibliometric analysis of books to model the structure and dynamics of science, aiming to inform the development of predictive models for research activities and their impact.

Contribution

It presents a new bibliometric approach applied to books, providing insights into scientific modeling and offering a foundation for designing better predictive models of science.

Findings

Analysis of a large collection of scientific books

Visualization of scientific knowledge structures

Discussion on informing new scientific models

Abstract

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.