The Semantic Units Framework, a technology-agnostic representational approach to FAIR and CLEAR knowledge infrastructures

Abstract

This manuscript introduces the Semantic Units Framework, a technology-agnostic representational approach to semantic modularization in which statements and compound meaning structures are treated as first-class semantic units with explicit boundaries, identity, and epistemic status. Motivated by recurring limitations of triple-centric and OWL-based knowledge graphs, the framework shifts the focus from isolated triples to coherent units of meaning that can be referenced, contextualized, and composed. To support scientific generalization beyond individual facts, the framework introduces instance-quantified resource categories (some-instance, most-instances, every-instance, all-instances), enabling explicit representation of existential, prototypical, and universal claims, as well as their negations and contextual qualifications. Combined with semantic units, this approach supports the representation of higher-order statements, epistemic stances, and structured scientific argumentation within a unified semantic model. Rather than proposing a new graph technology, the Semantic Units Framework provides a reusable conceptual foundation that can be realized across existing data and knowledge representation technologies and supports both machine-actionable reasoning and human-interpretable knowledge representation.