Towards an explanatory and computational theory of scientific discovery

TL;DR

This paper presents a comprehensive computational theory explaining how connecting disparate knowledge areas through associative networks fosters transformative scientific discoveries, integrating insights from multiple scientific disciplines.

Contribution

It introduces an extended concept of structural holes in associative networks, providing a new framework for understanding scientific creativity and discovery.

Findings

Connecting disparate knowledge patches promotes creativity.

Structural holes in associative networks facilitate scientific breakthroughs.

The theory unifies diverse perspectives on scientific change.

Abstract

We propose an explanatory and computational theory of transformative discoveries in science. The theory is derived from a recurring theme found in a diverse range of scientific change, scientific discovery, and knowledge diffusion theories in philosophy of science, sociology of science, social network analysis, and information science. The theory extends the concept of structural holes from social networks to a broader range of associative networks found in science studies, especially including networks that reflect underlying intellectual structures such as co-citation networks and collaboration networks. The central premise is that connecting otherwise disparate patches of knowledge is a valuable mechanism of creative thinking in general and transformative scientific discovery in particular.