Memetic/Metaphorical Digital Twins: Extending Knowledge Co-Creation Across Economics, Architecture, and Beyond

Area of Science:

• Information Science
• Knowledge Management
• Digital Twin Technology

Background:

• Existing digital twin typologies (Industrial, Human, Cognitive) are extended.
• MDTs embed cultural, organizational, and semiotic knowledge into digital frameworks.
• Addresses systemic challenges in communication, knowledge transfer, and design.

Purpose of the Study:

• Introduce Memetic/Metaphorical Digital Twins (MDTs) as a novel extension of digital twin typologies.
• Demonstrate MDTs' capability to address systemic challenges using economic and thermodynamic perspectives.
• Propose a framework for adaptive, transdisciplinary knowledge co-creation.

Main Methods:

• Utilizes Schlaile's economic perspectives and Mavromatidis's architectural lens.
• Develops a Digital Community Platform supporting decentralized Personal Knowledge Management Systems (PKMS).
• Employs a memetic approach with memes as replicable knowledge units, mimicking biological evolution.
• Proposes a Boundary Object Taxonomy to Omnify Memetic Storytelling (BOTTOMS).

Main Results:

• MDTs enable recombination and evolution of knowledge structures across disciplines.
• The Digital Community Platform integrates iterative KM cycles for knowledge co-creation.
• MDTs offer distributed, decentralized, and knowledge-worker-centric applications.
• A unified framework (BOTTOMS) is proposed for structuring and disseminating atomic units of meaning.

Conclusions:

• MDTs provide a universal framework for adaptive, transdisciplinary knowledge co-creation.
• The approach mimics biological evolution and ecosystem resilience in digital environments.
• Future developments include AI-supported curation and expanded boundary objects.