A new generation of science overlay maps with an application to the history of biosystematics

TL;DR

This paper introduces a novel text-mining framework called Topic Overlay Mapping (TOM) for visualizing and analyzing complex scientific discourses, demonstrated through the interdisciplinary debate on the species concept in biosystematics.

Contribution

It generalizes existing science overlay mapping methods to enable detailed exploration and measurement of cognitive complexity in scientific fields.

Findings

TOM effectively visualizes scientific discourse structures.

The framework allows for analysis of cognitive complexity over time.

Application to biosystematics reveals insights into interdisciplinary debates.

Abstract

The paper proposes a text-mining based analytical framework aiming at the cognitive organization of complex scientific discourses. The approach is based on models recently developed in science mapping, being a generalization of the so-called Science Overlay Mapping methodology, referred to as Topic Overlay Mapping (TOM). It is shown that via applications of TOM in visualization, document clustering, time series analysis etc. the in-depth exploration and even the measurement of cognitive complexity and its dynamics is feasible for scientific domains. As a use case, an empirical study is presented into the discovery of a long-standing complex, interdisciplinary discourse, the debate on the species concept in biosystematics.