Thermodynamics of Scientific Ontology

In this work, we propose a thermodynamic framework to analyze the creative potential of scientific fields by examining statistical data on the usage frequencies of scientific concepts within a corpus of publications from ArXiv. Using statistical mechanics and thermodynamics, we model the system of physical concepts that form the ontology of scientific field. We explore the relationship between Clausius entropy and Shannon entropy in this context, assuming the interaction of concepts through their pairwise mutual information. Our approach enables us to leverage methods from statistical physics to analyze information systems during knowledge production and transfer. We demonstrate that the coarse-grained frequencies of scientific concepts follow a generalized Boltzmann distribution, allowing for a thermodynamic description. This study calculates internal energy, Helmholtz free energy, temperature, and heat capacity for scientific concepts as closed thermodynamic systems, and maps the state space of the concepts-based knowledge network using data-driven thermodynamic diagrams. This framework advances the methods of computational theory of discovery by providing insights into the dynamics of scientific knowledge and the emergence of innovation.