MOteoria

MOteoria is a proposed interdisciplinary framework that seeks to integrate modeling practices, ontological commitments, and theory construction across scientific and applied domains. The term MOteoria combines modeling, ontology, and theory to emphasize the connections among representations, their underlying assumptions, and the explanations they yield. The framework aims to improve transparency, reproducibility, and cross-domain communication by making explicit how models map to ontologies and how both support theoretical claims.

Origin and development: MOteoria emerged in scholarly discussions during the 2020s, as researchers argued that inconsistencies among models, ontologies, and theories hinder comparability. It is not a single method but a family of approaches that share a commitment to explicit alignment among the three layers.

Key concepts: The core idea is to maintain three layers—modeling practices (formalisms, simulations), ontological commitments (the entities and relations used), and theoretical claims (explanations, predictions)—and to define mappings between them. It stresses explicit uncertainty handling, modular architecture, and iterative validation against empirical data. It often employs ontology engineering techniques to standardize terms across domains and fosters interoperability by using shared vocabularies.

Methodology and applications: Practically, applying MOteoria involves defining the problem, specifying ontological commitments, developing or reviewing models, deriving theoretical conclusions, and validating results against data. It has been applied in knowledge management, data science, AI system design, and science education to improve modeling discipline and understandability.

Criticism and reception: Some scholars caution that MOteoria can be overly abstract or burdensome to implement, especially in rapidly changing fields. Critics also point out difficulties in agreeing on ontologies and in maintaining consistency across evolving models. Proponents argue that the approach fosters clarity and auditability.