The Backbone of Digital Twins: Comprehensive Data Management Requirements

The exponential growth of data highlights the pivotal role of data management in emerging technologies. Meanwhile, digital twins are transitioning from conceptual discussions to industrial implementation. In order to enable robust and scalable solutions, digital twins require an architecture that integrates data management through holistic requirements. This study addresses this need by conducting a structured literature review to consolidate existing research. The analysis identified 39 requirements, organized into eight categories derived from the DAMA-DMBOK wheel. These categories align established data management best practices with the specific demands of digital twin systems. The resulting catalog of requirements contributes to theory and practice alike, providing a systematic foundation for future research and guiding the implementation of interoperable, operational digital twins.