UMOSU and UMOKWAI: An Ontological and Epistemic-Operational Model for the Classification of Reality and Knowledge

This paper presents UMOSU (Unified Model of Social Universe), an ontological model designed to classify phenomena according to the components that are necessary for their manifestation, and UMOKWAI (Unified Model of Knowledge With AI), an epistemic-operational model designed to classify bodies of knowledge according to the phenomena they investigate.The central proposition of the model is that phenomena should be classified primarily in terms of their becoming, rather than according to the material composition or presumed essence of the objects involved. UMOSU distinguishes four domains — the inorganic subuniverse, the subuniverse of life, the semiotic subuniverse, and the domain of complexity — separated by three ontological thresholds: the life threshold, the processing threshold, and the complexity threshold.The model further introduces five parameters — origin, relationship, shape, reality check, and the legality of free will — used to characterize six fundamental and eight derived phenomena. UMOKWAI applies this ontological structure to the classification of disciplines, distinguishing eight principal classes, K1–K8, ranging from inorganic sciences and technological disciplines to biological sciences, formal doctrines, speculative doctrines, and complex social and institutional disciplines.A principal aim of the model is to distinguish different epistemic conditions — falsifiable, formally demonstrable, non-falsifiable, and verifiable/interpretative — without assigning greater or lesser scientific value to different forms of knowledge. The model is proposed not as a replacement for existing disciplinary classifications, but as an ontological map capable of explaining why existing classifications frequently overlap.This paper is the foundational document of the UMOSU/UMOKWAI research programme, from which the subsequent deposits listed in the References section develop specific applications: an anti-hallucination operational ruleset, phenomenon-by-phenomenon reliability specifications, supervision and presentation routers for AI-generated drafts, and a comparison with the AI Regulation of the Municipality of Treviso.Keywords: UMOSU, UMOKWAI, ontology, epistemology, classification of knowledge, ontology of phenomena, interdisciplinarity, falsifiability, semiotics, social universe, artificial intelligence.