A New Approach to Information Hierarchy Based on Data Spaces and Intelligent Digital Twins: Cyclic Layers Model (CLM)

Abstract

The rapid evolution of the digital era exposes the limitations of traditional hierarchical information models, such as Ackoff’s DIKUW and Bellinger’s DIKW pyramid, which fail to fully address contemporary challenges in data management and ethical technology use. This study introduces the Cyclic Layers Model (CLM) as a unified, holistic alternative that consolidates fragmented knowledge management approaches into a single, dynamic framework. Drawing from bibliometric analysis of 1074 publications (1985–2025) across major databases, and narrowing to 535 relevant studies, the model restructures information flow through cyclic, interconnected layers that incorporate individual, organizational, and environmental factors. By integrating Data Spaces and Intelligent Digital Twins (IDTs), the model offers a comprehensive approach to addressing ethical AI deployment, data privacy, and sustainability issues. This framework not only advances theoretical under-standing in knowledge management but also provides practical pathways for responsible decision-making in sectors such as healthcare and smart cities. CLM thus sets the stage for future multidisciplinary research aimed at designing ethically and culturally aware intelligent systems.