To develop systemic solutions that are both viable and compatible with sustainable developmentSustainable development goals, expertsExperts (specialists and generalists alike) and our society as-a-whole must acknowledge that we live in complex dynamic systemsComplex dynamic systems (CDS), i.e., big problems require holistic approaches and functional coordination between different types of expertiseExpertise and sources of knowledge. And this, in turn, is a major epistemic challenge, one that is particularly visible in sustainabilitySustainability studies and informationInformation science but exists in all of science by definition: scientific research follows the Maximum Entropy PrincipleMaximum entropy principle (MEP) according to which a model or theory must be as simple as possible and not simpler–something easier said than done. In sum, in daily practice, science ‘tracks the truth’ but also remains a social phenomenon tied to a dynamic equilibrium between search (exploration) and utility (exploitation), and this ambidexterity is not just a ‘nice to have’ but a ‘must’: we need to understand how relevant concepts emerge, evolve and interconnect in the Big Picture. In this context, the paper hereby reviews the potential of the physical notion of EntropyEntropy to serve as an organizational principle and start-basis for ‘Knowledge MappingKnowledge mapping’ (KM) and knowledge integration in-and-between sustainabilitySustainability studies and informationInformation science. In a nutshell, this targeted comparative study of the fundamentals shows (and makes explicit the basic intuition) that EntropyEntropy grounds not only the fundamental notion of informationInformation (and its manifestations in natural and social systems; inter alia, providing a platform for good decision-making) but also the relatively-recent and still-developing systemic perspective on sustainabilitySustainability, whose perspective (it is important to remind and highlight in the context of this analysis) starts from the recognition that any economic system is a sub-system of a social system while any social system is a sub-system of a natural (biophysical) system. The study concludes that a (Fundamental MathematicsCategory Theory (Mathematics))-enabled EntropyEntropy-based ranking of Categories appears to be a natural strategy for KM per se and, more broadly, for finding the right combination of relevance and managerial efficiency in Research, Development and Innovation (RDIResearch, Development and Innovation (RDI)) projects and in Knowledge OrganizationKnowledge organization (KO) more generally.

Maximum Entropy: Epistemic Grounds Shared by Sustainability Studies and Information Science

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发表日期：

2026年

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Ioan M. Ciumasu

摘要

To develop systemic solutions that are both viable and compatible with sustainable developmentSustainable development goals, expertsExperts (specialists and generalists alike) and our society as-a-whole must acknowledge that we live in complex dynamic systemsComplex dynamic systems (CDS), i.e., big problems require holistic approaches and functional coordination between different types of expertiseExpertise and sources of knowledge. And this, in turn, is a major epistemic challenge, one that is particularly visible in sustainabilitySustainability studies and informationInformation science but exists in all of science by definition: scientific research follows the Maximum Entropy PrincipleMaximum entropy principle (MEP) according to which a model or theory must be as simple as possible and not simpler–something easier said than done. In sum, in daily practice, science ‘tracks the truth’ but also remains a social phenomenon tied to a dynamic equilibrium between search (exploration) and utility (exploitation), and this ambidexterity is not just a ‘nice to have’ but a ‘must’: we need to understand how relevant concepts emerge, evolve and interconnect in the Big Picture. In this context, the paper hereby reviews the potential of the physical notion of EntropyEntropy to serve as an organizational principle and start-basis for ‘Knowledge MappingKnowledge mapping’ (KM) and knowledge integration in-and-between sustainabilitySustainability studies and informationInformation science. In a nutshell, this targeted comparative study of the fundamentals shows (and makes explicit the basic intuition) that EntropyEntropy grounds not only the fundamental notion of informationInformation (and its manifestations in natural and social systems; inter alia, providing a platform for good decision-making) but also the relatively-recent and still-developing systemic perspective on sustainabilitySustainability, whose perspective (it is important to remind and highlight in the context of this analysis) starts from the recognition that any economic system is a sub-system of a social system while any social system is a sub-system of a natural (biophysical) system. The study concludes that a (Fundamental MathematicsCategory Theory (Mathematics))-enabled EntropyEntropy-based ranking of Categories appears to be a natural strategy for KM per se and, more broadly, for finding the right combination of relevance and managerial efficiency in Research, Development and Innovation (RDIResearch, Development and Innovation (RDI)) projects and in Knowledge OrganizationKnowledge organization (KO) more generally.